Training in progress, step 3000

.gitattributes

@@ -32,3 +32,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+wandb/run-20250212_152709-lejyafmi/run-lejyafmi.wandb filter=lfs diff=lfs merge=lfs -text

config.json

@@ -31,7 +31,7 @@
   "mask_time_length": 10,
   "mask_time_min_masks": 2,
   "mask_time_prob": 0.05,
-  "max_length": 448,
+  "max_length": null,
   "max_source_positions": 1500,
   "max_target_positions": 448,
   "median_filter_width": 7,
@@ -41,7 +41,7 @@
   "pad_token_id": 50257,
   "scale_embedding": false,
   "torch_dtype": "float32",
-  "transformers_version": "4.46.0.dev0",
+  "transformers_version": "4.49.0.dev0",
   "use_cache": false,
   "use_weighted_layer_sum": false,
   "vocab_size": 51865

inspect_dataset.py

@@ -0,0 +1,26 @@
+from datasets import load_dataset
+import json
+
+# Load the first few examples of the dataset
+dataset = load_dataset("asierhv/composite_corpus_eu_v2.1", split="train", streaming=True)
+
+# Get the first example
+examples = []
+for i, example in enumerate(dataset):
+    if i >= 3:  # Get first 3 examples
+        break
+    examples.append(example)
+
+# Print the structure and content
+for i, example in enumerate(examples):
+    print(f"\nExample {i+1}:")
+    for key, value in example.items():
+        if key == "audio":
+            print(f"audio keys: {value.keys()}")
+            for audio_key, audio_value in value.items():
+                if isinstance(audio_value, bytes) or isinstance(audio_value, memoryview):
+                    print(f"  {audio_key}: <binary data>")
+                else:
+                    print(f"  {audio_key}: {audio_value}")
+        else:
+            print(f"{key}: {value}")

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:51160e502a9753fabd3f154ffcebb40049941544eb344c4b8fc8243205072f73
+oid sha256:4d2fd3b1746a32b70ee58ee1a3c90a88042e6300b79bcf3fd6d5bfc260af06f0
 size 966995080

requirements.txt

@@ -0,0 +1,11 @@
+torch>=1.7
+torchaudio
+git+https://github.com/huggingface/transformers
+git+https://github.com/huggingface/datasets
+librosa
+jiwer
+evaluate>=0.3.0
+more-itertools
+tensorboard
+accelerate>=0.26.0
+wandb>=0.19.6

run.sh

@@ -1,12 +1,12 @@
+WANDB_PROJECT=whisper-small-eu \
 python run_speech_recognition_seq2seq_streaming.py \
 	--model_name_or_path="openai/whisper-small" \
-	--dataset_name="mozilla-foundation/common_voice_17_0" \
-	--dataset_config_name="eu" \
+	--dataset_name="asierhv/composite_corpus_eu_v2.1" \
 	--language="basque" \
-	--train_split_name="train+validation" \
-	--eval_split_name="test" \
+	--train_split_name="train" \
+	--eval_split_name="dev_parl+test_parl+test_cv+test_oslr" \
 	--model_index_name="Whisper Small Basque" \
-	--max_steps="5000" \
+	--max_steps="8000" \
 	--output_dir="./" \
 	--per_device_train_batch_size="32" \
 	--per_device_eval_batch_size="16" \
@@ -21,6 +21,7 @@ python run_speech_recognition_seq2seq_streaming.py \
 	--generation_max_length="225" \
 	--length_column_name="input_length" \
 	--max_duration_in_seconds="30" \
+	--audio_column_name="audio" \
 	--text_column_name="sentence" \
 	--freeze_feature_encoder="False" \
 	--report_to="tensorboard" \
@@ -36,4 +37,6 @@ python run_speech_recognition_seq2seq_streaming.py \
 	--do_normalize_eval \
 	--streaming \
 	--use_auth_token \
-	--push_to_hub
+	--push_to_hub \
+	--report_to "wandb" \
+	--run_name "whisper-small-eu"

run_cv.sh

@@ -0,0 +1,39 @@
+python run_speech_recognition_seq2seq_streaming.py \
+	--model_name_or_path="openai/whisper-small" \
+	--dataset_name="mozilla-foundation/common_voice_17_0" \
+	--dataset_config_name="eu" \
+	--language="basque" \
+	--train_split_name="train+validation" \
+	--eval_split_name="test" \
+	--model_index_name="Whisper Small Basque" \
+	--max_steps="5000" \
+	--output_dir="./" \
+	--per_device_train_batch_size="32" \
+	--per_device_eval_batch_size="16" \
+	--gradient_accumulation_steps="1" \
+	--logging_steps="25" \
+	--learning_rate="1e-5" \
+	--warmup_steps="500" \
+	--evaluation_strategy="steps" \
+	--eval_steps="1000" \
+	--save_strategy="steps" \
+	--save_steps="1000" \
+	--generation_max_length="225" \
+	--length_column_name="input_length" \
+	--max_duration_in_seconds="30" \
+	--text_column_name="sentence" \
+	--freeze_feature_encoder="False" \
+	--report_to="tensorboard" \
+	--metric_for_best_model="wer" \
+	--greater_is_better="False" \
+	--load_best_model_at_end \
+	--gradient_checkpointing \
+	--fp16 \
+	--overwrite_output_dir \
+	--do_train \
+	--do_eval \
+	--predict_with_generate \
+	--do_normalize_eval \
+	--streaming \
+	--use_auth_token \
+	--push_to_hub

run_speech_recognition_seq2seq_streaming.py

@@ -25,6 +25,7 @@ import os
 import sys
 from dataclasses import dataclass, field
 from typing import Any, Dict, List, Optional, Union
+import numpy
 
 import datasets
 import torch
@@ -265,25 +266,58 @@ class DataCollatorSpeechSeq2SeqWithPadding:
         return batch
 
 
-def load_maybe_streaming_dataset(dataset_name, dataset_config_name, split="train", streaming=True, **kwargs):
+def load_maybe_streaming_dataset(dataset_name, dataset_config_name, data_args, split="train", streaming=True, **kwargs):
     """
-    Utility function to load a dataset in streaming mode. For datasets with multiple splits,
-    each split is loaded individually and then splits combined by taking alternating examples from
-    each (interleaving).
+    Utility function to load a dataset in streaming mode.
     """
+    logger.info(f"Loading dataset {dataset_name} split {split} (streaming={streaming})")
+    
+    def load_single_split(split_name):
+        logger.info(f"Loading split: {split_name}")
+        ds = load_dataset(
+            dataset_name, 
+            dataset_config_name, 
+            split=split_name, 
+            streaming=streaming, 
+            trust_remote_code=True, 
+            **kwargs
+        )
+        
+        # Add validation transform to ensure consistent audio format
+        def validate_example(example):
+            if not isinstance(example[data_args.audio_column_name], dict):
+                example[data_args.audio_column_name] = {
+                    'array': example[data_args.audio_column_name].array,
+                    'sampling_rate': example[data_args.audio_column_name].sampling_rate,
+                    'path': getattr(example[data_args.audio_column_name], 'path', None)
+                }
+            return example
+            
+        ds = ds.map(validate_example)
+        
+        # Log first example structure for debugging
+        try:
+            first_example = next(iter(ds))
+            logger.info(f"First example from {split_name}:")
+            logger.info(f"  Keys: {first_example.keys()}")
+            if data_args.audio_column_name in first_example:
+                audio = first_example[data_args.audio_column_name]
+                logger.info(f"  Audio type: {type(audio)}")
+                if isinstance(audio, dict):
+                    logger.info(f"  Audio keys: {audio.keys()}")
+                    logger.info(f"  Array type: {type(audio['array']) if 'array' in audio else 'missing'}")
+        except Exception as e:
+            logger.warning(f"Could not inspect first example from {split_name}: {e}")
+            
+        return ds
+    
     if "+" in split:
-        # load multiple splits separated by the `+` symbol with streaming mode
-        dataset_splits = [
-            load_dataset(dataset_name, dataset_config_name, split=split_name, streaming=streaming, trust_remote_code=True, **kwargs)
-            for split_name in split.split("+")
-        ]
-        # interleave multiple splits to form one dataset
-        interleaved_dataset = interleave_datasets(dataset_splits)
-        return interleaved_dataset
+        # Load and validate each split individually
+        dataset_splits = [load_single_split(split_name) for split_name in split.split("+")]
+        # Interleave datasets
+        return interleave_datasets(dataset_splits)
     else:
-        # load a single split *with* streaming mode
-        dataset = load_dataset(dataset_name, dataset_config_name, split=split, streaming=streaming, trust_remote_code=True, **kwargs)
-        return dataset
+        return load_single_split(split)
 
 
 def main():
@@ -356,37 +390,39 @@ def main():
         raw_datasets["train"] = load_maybe_streaming_dataset(
             data_args.dataset_name,
             data_args.dataset_config_name,
+            data_args,
             split=data_args.train_split_name,
-            # xezpeleta
-            #use_auth_token=True if model_args.use_auth_token else None,
             streaming=data_args.streaming,
         )
 
+        # Get features from train dataset since it's guaranteed to exist if do_train is True
+        train_dataset = raw_datasets["train"]
+        first_example = next(iter(train_dataset))
+        raw_datasets_features = list(first_example.keys())
+
+        if data_args.audio_column_name not in raw_datasets_features:
+            raise ValueError(
+                f"--audio_column_name '{data_args.audio_column_name}' not found in dataset '{data_args.dataset_name}'. "
+                "Make sure to set `--audio_column_name` to the correct audio column - one of "
+                f"{', '.join(raw_datasets_features)}."
+            )
+
+        if data_args.text_column_name not in raw_datasets_features:
+            raise ValueError(
+                f"--text_column_name {data_args.text_column_name} not found in dataset '{data_args.dataset_name}'. "
+                "Make sure to set `--text_column_name` to the correct text column - one of "
+                f"{', '.join(raw_datasets_features)}."
+            )
+
     if training_args.do_eval:
         raw_datasets["eval"] = load_maybe_streaming_dataset(
             data_args.dataset_name,
             data_args.dataset_config_name,
+            data_args,
             split=data_args.eval_split_name,
-            #use_auth_token=True if model_args.use_auth_token else None,
             streaming=data_args.streaming,
         )
 
-    raw_datasets_features = list(next(iter(raw_datasets.values())).features.keys())
-
-    if data_args.audio_column_name not in raw_datasets_features:
-        raise ValueError(
-            f"--audio_column_name '{data_args.audio_column_name}' not found in dataset '{data_args.dataset_name}'. "
-            "Make sure to set `--audio_column_name` to the correct audio column - one of "
-            f"{', '.join(raw_datasets_features)}."
-        )
-
-    if data_args.text_column_name not in raw_datasets_features:
-        raise ValueError(
-            f"--text_column_name {data_args.text_column_name} not found in dataset '{data_args.dataset_name}'. "
-            "Make sure to set `--text_column_name` to the correct text column - one of "
-            f"{', '.join(raw_datasets_features)}."
-        )
-
     # 5. Load pretrained model, tokenizer, and feature extractor
     #
     # Distributed training:
@@ -438,14 +474,12 @@ def main():
         tokenizer.set_prefix_tokens(language=data_args.language, task=data_args.task)
 
     # 6. Resample speech dataset if necessary
-    dataset_sampling_rate = next(iter(raw_datasets.values())).features[data_args.audio_column_name].sampling_rate
-    if dataset_sampling_rate != feature_extractor.sampling_rate:
-        raw_datasets = raw_datasets.cast_column(
-            data_args.audio_column_name, datasets.features.Audio(sampling_rate=feature_extractor.sampling_rate)
-        )
+    # For streaming datasets with audio bytes, sampling rate is handled in prepare_dataset
+    logger.info("Using feature extractor sampling rate: %d", feature_extractor.sampling_rate)
+    dataset_sampling_rate = feature_extractor.sampling_rate
 
     # 7. Preprocessing the datasets.
-    # We need to read the audio files as arrays and tokenize the targets.
+    logger.info("Starting dataset preprocessing")
     max_input_length = data_args.max_duration_in_seconds * feature_extractor.sampling_rate
     min_input_length = data_args.min_duration_in_seconds * feature_extractor.sampling_rate
     audio_column_name = data_args.audio_column_name
@@ -469,20 +503,59 @@ def main():
             else raw_datasets["eval"].select(range(data_args.max_eval_samples))
         )
 
+    # Inspect dataset before processing
+    for split, dataset in raw_datasets.items():
+        try:
+            first_example = next(iter(dataset))
+            logger.info(f"First example from {split} before processing:")
+            logger.info(f"Keys: {first_example.keys()}")
+            if audio_column_name in first_example:
+                audio_data = first_example[audio_column_name]
+                logger.info(f"Audio column type: {type(audio_data)}")
+                if isinstance(audio_data, dict):
+                    logger.info(f"Audio keys: {audio_data.keys()}")
+        except Exception as e:
+            logger.warning(f"Could not inspect first example from {split}: {e}")
+
     def prepare_dataset(batch):
-        # process audio
-        sample = batch[audio_column_name]
-        inputs = feature_extractor(sample["array"], sampling_rate=sample["sampling_rate"])
-        # process audio length
-        batch[model_input_name] = inputs.get(model_input_name)[0]
-        batch["input_length"] = len(sample["array"])
-
-        # process targets
-        input_str = batch[text_column_name].lower() if do_lower_case else batch[text_column_name]
-        if do_remove_punctuation:
-            input_str = normalizer(input_str).strip()
-        batch["labels"] = tokenizer(input_str).input_ids
-        return batch
+        try:
+            # Validate audio format
+            audio = batch[audio_column_name]
+            
+            # Load audio from bytes if needed
+            if isinstance(audio, dict) and 'bytes' in audio:
+                import io
+                import soundfile as sf
+                audio_bytes = io.BytesIO(audio['bytes'])
+                audio_array, sampling_rate = sf.read(audio_bytes)
+                audio = {'array': audio_array, 'sampling_rate': sampling_rate}
+            
+            # Process audio through feature extractor
+            inputs = feature_extractor(audio['array'], sampling_rate=audio['sampling_rate'])
+            batch["input_length"] = len(audio['array'])
+            batch[model_input_name] = inputs[model_input_name][0]
+            
+            # Process text
+            input_str = batch[text_column_name].lower() if do_lower_case else batch[text_column_name]
+            if do_remove_punctuation:
+                input_str = normalizer(input_str).strip()
+            batch["labels"] = tokenizer(input_str).input_ids
+            
+            return batch
+            
+        except Exception as e:
+            logger.error(f"Error processing batch in prepare_dataset:")
+            logger.error(f"  Error type: {type(e).__name__}")
+            logger.error(f"  Error message: {str(e)}")
+            logger.error(f"  Batch keys: {list(batch.keys())}")
+            if audio_column_name in batch:
+                audio_data = batch[audio_column_name]
+                logger.error(f"  Audio type: {type(audio_data)}")
+                if isinstance(audio_data, dict):
+                    logger.error(f"  Audio keys: {list(audio_data.keys())}")
+                elif hasattr(audio_data, '__dict__'):
+                    logger.error(f"  Audio attributes: {dir(audio_data)}")
+            raise
 
     with training_args.main_process_first(desc="dataset map pre-processing"):
         vectorized_datasets = raw_datasets.map(
@@ -490,6 +563,16 @@ def main():
             remove_columns=raw_datasets_features,
         ).with_format("torch")
 
+        # Inspect vectorized dataset
+        for split, dataset in vectorized_datasets.items():
+            try:
+                first_example = next(iter(dataset))
+                logger.info(f"First example from {split} after processing:")
+                logger.info(f"Keys: {first_example.keys()}")
+                logger.info(f"Types: {', '.join(f'{k}: {type(v)}' for k, v in first_example.items())}")
+            except Exception as e:
+                logger.warning(f"Could not inspect first example from vectorized {split}: {e}")
+
         if training_args.do_train and data_args.streaming:
             # manually shuffle if streaming (done by the trainer for non-streaming)
             vectorized_datasets["train"] = vectorized_datasets["train"].shuffle(
@@ -551,7 +634,13 @@ def main():
     # Trainer callback to reinitialise and reshuffle the streamable datasets at the beginning of each epoch
     # Only required for streaming: Trainer automatically shuffles non-streaming datasets
     class ShuffleCallback(TrainerCallback):
-        def on_epoch_begin(self, args, state, control, train_dataloader, **kwargs):
+        def on_train_begin(self, args, state, control, **kwargs):
+            self.trainer = kwargs.get('trainer')
+
+        def on_epoch_begin(self, args, state, control, **kwargs):
+            if not hasattr(self, "trainer") or not hasattr(self.trainer, "train_dataloader") or self.trainer.train_dataloader is None:
+                return
+            train_dataloader = self.trainer.train_dataloader
             if isinstance(train_dataloader.dataset, IterableDatasetShard):
                 pass  # set_epoch() is handled by the Trainer
             elif isinstance(train_dataloader.dataset, IterableDataset):
@@ -563,7 +652,7 @@ def main():
         args=training_args,
         train_dataset=vectorized_datasets["train"] if training_args.do_train else None,
         eval_dataset=vectorized_datasets["eval"] if training_args.do_eval else None,
-        tokenizer=feature_extractor,
+        processing_class=feature_extractor,
         data_collator=data_collator,
         compute_metrics=compute_metrics if training_args.predict_with_generate else None,
         callbacks=[ShuffleCallback()] if data_args.streaming else None,

run_speech_recognition_seq2seq_streaming_cv.py

@@ -0,0 +1,657 @@
+#!/usr/bin/env python
+# coding=utf-8
+# Copyright 2022 The HuggingFace Team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""
+Fine-tuning the library models for sequence to sequence speech recognition
+with 🤗 Datasets' streaming mode.
+"""
+# You can also adapt this script for your own sequence to sequence speech
+# recognition task. Pointers for this are left as comments.
+
+import logging
+import os
+import sys
+from dataclasses import dataclass, field
+from typing import Any, Dict, List, Optional, Union
+import numpy
+
+import datasets
+import torch
+from datasets import DatasetDict, IterableDatasetDict, interleave_datasets, load_dataset
+from torch.utils.data import IterableDataset
+
+import evaluate
+import transformers
+from transformers import (
+    AutoConfig,
+    AutoFeatureExtractor,
+    AutoModelForSpeechSeq2Seq,
+    AutoProcessor,
+    AutoTokenizer,
+    HfArgumentParser,
+    Seq2SeqTrainer,
+    Seq2SeqTrainingArguments,
+    TrainerCallback,
+    set_seed,
+)
+from transformers.models.whisper.english_normalizer import BasicTextNormalizer
+from transformers.trainer_pt_utils import IterableDatasetShard
+from transformers.trainer_utils import get_last_checkpoint, is_main_process
+from transformers.utils import check_min_version, send_example_telemetry
+from transformers.utils.versions import require_version
+
+
+# Will error if the minimal version of Transformers is not installed. Remove at your own risks.
+check_min_version("4.25.0.dev0")
+
+require_version("datasets>=1.18.2", "To fix: pip install -r examples/pytorch/speech-recognition/requirements.txt")
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass
+class ModelArguments:
+    """
+    Arguments pertaining to which model/config/tokenizer we are going to fine-tune from.
+    """
+
+    model_name_or_path: str = field(
+        metadata={"help": "Path to pretrained model or model identifier from huggingface.co/models"}
+    )
+    config_name: Optional[str] = field(
+        default=None, metadata={"help": "Pretrained config name or path if not the same as model_name"}
+    )
+    tokenizer_name: Optional[str] = field(
+        default=None, metadata={"help": "Pretrained tokenizer name or path if not the same as model_name"}
+    )
+    feature_extractor_name: Optional[str] = field(
+        default=None, metadata={"help": "feature extractor name or path if not the same as model_name"}
+    )
+    cache_dir: Optional[str] = field(
+        default=None,
+        metadata={"help": "Where to store the pretrained models downloaded from huggingface.co"},
+    )
+    use_fast_tokenizer: bool = field(
+        default=True,
+        metadata={"help": "Whether to use one of the fast tokenizer (backed by the tokenizers library) or not."},
+    )
+    model_revision: str = field(
+        default="main",
+        metadata={"help": "The specific model version to use (can be a branch name, tag name or commit id)."},
+    )
+    use_auth_token: bool = field(
+        default=False,
+        metadata={
+            "help": (
+                "Will use the token generated when running `huggingface-cli login` (necessary to use this script "
+                "with private models)."
+            )
+        },
+    )
+    freeze_feature_encoder: bool = field(
+        default=True, metadata={"help": "Whether to freeze the feature encoder layers of the model."}
+    )
+    freeze_encoder: bool = field(
+        default=False, metadata={"help": "Whether to freeze the entire encoder of the seq2seq model."}
+    )
+    forced_decoder_ids: List[List[int]] = field(
+        default=None,
+        metadata={
+            "help": (
+                "A list of pairs of integers which indicates a mapping from generation indices to token indices "
+                "that will be forced before sampling. For example, [[0, 123]] means the first generated token "
+                "will always be a token of index 123."
+            )
+        },
+    )
+    suppress_tokens: List[int] = field(
+        default=None, metadata={"help": "A list of tokens that will be suppressed at generation."}
+    )
+    model_index_name: str = field(default=None, metadata={"help": "Pretty name for the model card."})
+
+
+@dataclass
+class DataTrainingArguments:
+    """
+    Arguments pertaining to what data we are going to input our model for training and eval.
+    """
+
+    dataset_name: str = field(
+        default=None, metadata={"help": "The name of the dataset to use (via the datasets library)."}
+    )
+    dataset_config_name: Optional[str] = field(
+        default=None, metadata={"help": "The configuration name of the dataset to use (via the datasets library)."}
+    )
+    text_column: Optional[str] = field(
+        default=None,
+        metadata={"help": "The name of the column in the datasets containing the full texts (for summarization)."},
+    )
+    max_train_samples: Optional[int] = field(
+        default=None,
+        metadata={
+            "help": (
+                "For debugging purposes or quicker training, truncate the number of training examples to this "
+                "value if set."
+            )
+        },
+    )
+    max_eval_samples: Optional[int] = field(
+        default=None,
+        metadata={
+            "help": (
+                "For debugging purposes or quicker training, truncate the number of evaluation examples to this "
+                "value if set."
+            )
+        },
+    )
+    audio_column_name: str = field(
+        default="audio",
+        metadata={"help": "The name of the dataset column containing the audio data. Defaults to 'audio'"},
+    )
+    text_column_name: str = field(
+        default="text",
+        metadata={"help": "The name of the dataset column containing the text data. Defaults to 'text'"},
+    )
+    max_duration_in_seconds: float = field(
+        default=20.0,
+        metadata={
+            "help": (
+                "Truncate audio files that are longer than `max_duration_in_seconds` seconds to"
+                " 'max_duration_in_seconds`"
+            )
+        },
+    )
+    min_duration_in_seconds: float = field(
+        default=0.0, metadata={"help": "Filter audio files that are shorter than `min_duration_in_seconds` seconds"}
+    )
+    train_split_name: str = field(
+        default="train",
+        metadata={
+            "help": "The name of the training data set split to use (via the datasets library). Defaults to 'train'"
+        },
+    )
+    eval_split_name: str = field(
+        default="test",
+        metadata={
+            "help": "The name of the training data set split to use (via the datasets library). Defaults to 'train'"
+        },
+    )
+    do_lower_case: bool = field(
+        default=False,
+        metadata={"help": "Whether the target text should be lower cased."},
+    )
+    do_remove_punctuation: bool = field(
+        default=False,
+        metadata={"help": "Whether the target text should be striped of punctuation."},
+    )
+    do_normalize_eval: bool = field(
+        default=True,
+        metadata={"help": "Whether to normalise the references and predictions in the eval WER calculation."},
+    )
+    language: str = field(
+        default=None,
+        metadata={
+            "help": (
+                "Language for multilingual fine-tuning. This argument should be set for multilingual fine-tuning "
+                "only. For English speech recognition, it should be set to `None`."
+            )
+        },
+    )
+    task: str = field(
+        default="transcribe",
+        metadata={"help": "Task, either `transcribe` for speech recognition or `translate` for speech translation."},
+    )
+    shuffle_buffer_size: Optional[int] = field(
+        default=500,
+        metadata={
+            "help": (
+                "The number of streamed examples to download before shuffling them. The large the buffer, "
+                "the closer it is to real offline shuffling."
+            )
+        },
+    )
+    streaming: bool = field(
+        default=True,
+        metadata={"help": "Whether to use streaming mode to load and pre-process the data."},
+    )
+
+
+@dataclass
+class DataCollatorSpeechSeq2SeqWithPadding:
+    """
+    Data collator that will dynamically pad the inputs received.
+    Args:
+        processor ([`WhisperProcessor`])
+            The processor used for processing the data.
+        decoder_start_token_id (`int`)
+            The begin-of-sentence of the decoder.
+    """
+
+    processor: Any
+    decoder_start_token_id: int
+
+    def __call__(self, features: List[Dict[str, Union[List[int], torch.Tensor]]]) -> Dict[str, torch.Tensor]:
+        # split inputs and labels since they have to be of different lengths and need
+        # different padding methods
+        model_input_name = self.processor.model_input_names[0]
+        input_features = [{model_input_name: feature[model_input_name]} for feature in features]
+        label_features = [{"input_ids": feature["labels"]} for feature in features]
+
+        batch = self.processor.feature_extractor.pad(input_features, return_tensors="pt")
+
+        labels_batch = self.processor.tokenizer.pad(label_features, return_tensors="pt")
+
+        # replace padding with -100 to ignore loss correctly
+        labels = labels_batch["input_ids"].masked_fill(labels_batch.attention_mask.ne(1), -100)
+
+        # if bos token is appended in previous tokenization step,
+        # cut bos token here as it's append later anyways
+        if (labels[:, 0] == self.decoder_start_token_id).all().cpu().item():
+            labels = labels[:, 1:]
+
+        batch["labels"] = labels
+
+        return batch
+
+
+def load_maybe_streaming_dataset(dataset_name, dataset_config_name, split="train", streaming=True, **kwargs):
+    """
+    Utility function to load a dataset in streaming mode. For datasets with multiple splits,
+    each split is loaded individually and then splits combined by taking alternating examples from
+    each (interleaving).
+    """
+    if ("+" in split):
+        # load multiple splits separated by the `+` symbol with streaming mode
+        dataset_splits = [
+            load_dataset(dataset_name, dataset_config_name, split=split_name, streaming=streaming, trust_remote_code=True, **kwargs)
+            for split_name in split.split("+")
+        ]
+        # interleave multiple splits to form one dataset
+        interleaved_dataset = interleave_datasets(dataset_splits)
+        return interleaved_dataset
+    else:
+        # load a single split *with* streaming mode
+        dataset = load_dataset(dataset_name, dataset_config_name, split=split, streaming=streaming, trust_remote_code=True, **kwargs)
+        return dataset
+
+
+def main():
+    # 1. Parse input arguments
+    # See all possible arguments in src/transformers/training_args.py
+    # or by passing the --help flag to this script.
+    # We now keep distinct sets of args, for a cleaner separation of concerns.
+    parser = HfArgumentParser((ModelArguments, DataTrainingArguments, Seq2SeqTrainingArguments))
+
+    if len(sys.argv) == 2 and sys.argv[1].endswith(".json"):
+        # If we pass only one argument to the script and it's the path to a json file,
+        # let's parse it to get our arguments.
+        model_args, data_args, training_args = parser.parse_json_file(json_file=os.path.abspath(sys.argv[1]))
+    else:
+        model_args, data_args, training_args = parser.parse_args_into_dataclasses()
+
+    # Sending telemetry. Tracking the example usage helps us better allocate resources to maintain them. The
+    # information sent is the one passed as arguments along with your Python/PyTorch versions.
+    send_example_telemetry("run_speech_recognition_seq2seq_streaming", model_args, data_args)
+
+    # 2. Setup logging
+    logging.basicConfig(
+        format="%(asctime)s - %(levelname)s - %(name)s - %(message)s",
+        datefmt="%m/%d/%Y %H:%M:%S",
+        handlers=[logging.StreamHandler(sys.stdout)],
+    )
+    log_level = training_args.get_process_log_level()
+    logger.setLevel(log_level)
+    datasets.utils.logging.set_verbosity(log_level)
+    transformers.utils.logging.set_verbosity(log_level)
+    transformers.utils.logging.enable_default_handler()
+    transformers.utils.logging.enable_explicit_format()
+
+    logger.setLevel(logging.INFO if is_main_process(training_args.local_rank) else logging.WARN)
+
+    # Log on each process the small summary:
+    logger.warning(
+        f"Process rank: {training_args.local_rank}, device: {training_args.device}, n_gpu: {training_args.n_gpu}"
+        f"distributed training: {bool(training_args.local_rank != -1)}, 16-bits training: {training_args.fp16}"
+    )
+    logger.info(f"Training/evaluation parameters {training_args}")
+
+    # Set the verbosity to info of the Transformers logger (on main process only):
+    if is_main_process(training_args.local_rank):
+        transformers.utils.logging.set_verbosity_info()
+    logger.info("Training/evaluation parameters %s", training_args)
+
+    # 3. Detecting last checkpoint and eventually continue from last checkpoint
+    last_checkpoint = None
+    if os.path.isdir(training_args.output_dir) and training_args.do_train and not training_args.overwrite_output_dir:
+        last_checkpoint = get_last_checkpoint(training_args.output_dir)
+        if last_checkpoint is None and len(os.listdir(training_args.output_dir)) > 0:
+            raise ValueError(
+                f"Output directory ({training_args.output_dir}) already exists and is not empty. "
+                "Use --overwrite_output_dir to overcome."
+            )
+        elif last_checkpoint is not None and training_args.resume_from_checkpoint is None:
+            logger.info(
+                f"Checkpoint detected, resuming training at {last_checkpoint}. To avoid this behavior, change "
+                "the `--output_dir` or add `--overwrite_output_dir` to train from scratch."
+            )
+
+    # Set seed before initializing model.
+    set_seed(training_args.seed)
+
+    # 4. Load dataset
+    raw_datasets = IterableDatasetDict() if data_args.streaming else DatasetDict()
+
+    if training_args.do_train:
+        raw_datasets["train"] = load_maybe_streaming_dataset(
+            data_args.dataset_name,
+            data_args.dataset_config_name,
+            split=data_args.train_split_name,
+            #use_auth_token=True if model_args.use_auth_token else None,
+            streaming=data_args.streaming,
+        )
+
+    if training_args.do_eval:
+        raw_datasets["eval"] = load_maybe_streaming_dataset(
+            data_args.dataset_name,
+            data_args.dataset_config_name,
+            split=data_args.eval_split_name,
+            #use_auth_token=True if model_args.use_auth_token else None,
+            streaming=data_args.streaming,
+        )
+
+    raw_datasets_features = list(next(iter(raw_datasets.values())).features.keys())
+
+    if data_args.audio_column_name not in raw_datasets_features:
+        raise ValueError(
+            f"--audio_column_name '{data_args.audio_column_name}' not found in dataset '{data_args.dataset_name}'. "
+            "Make sure to set `--audio_column_name` to the correct audio column - one of "
+            f"{', '.join(raw_datasets_features)}."
+        )
+
+    if data_args.text_column_name not in raw_datasets_features:
+        raise ValueError(
+            f"--text_column_name {data_args.text_column_name} not found in dataset '{data_args.dataset_name}'. "
+            "Make sure to set `--text_column_name` to the correct text column - one of "
+            f"{', '.join(raw_datasets_features)}."
+        )
+
+    # 5. Load pretrained model, tokenizer, and feature extractor
+    #
+    # Distributed training:
+    # The .from_pretrained methods guarantee that only one local process can concurrently
+    config = AutoConfig.from_pretrained(
+        model_args.config_name if model_args.config_name else model_args.model_name_or_path,
+        cache_dir=model_args.cache_dir,
+        revision=model_args.model_revision,
+        use_auth_token=True if model_args.use_auth_token else None,
+    )
+
+    config.update({"forced_decoder_ids": model_args.forced_decoder_ids, "suppress_tokens": model_args.suppress_tokens})
+
+    if training_args.gradient_checkpointing:
+        config.update({"use_cache": False})
+
+    feature_extractor = AutoFeatureExtractor.from_pretrained(
+        model_args.feature_extractor_name if model_args.feature_extractor_name else model_args.model_name_or_path,
+        cache_dir=model_args.cache_dir,
+        revision=model_args.model_revision,
+        use_auth_token=True if model_args.use_auth_token else None,
+    )
+    tokenizer = AutoTokenizer.from_pretrained(
+        model_args.tokenizer_name if model_args.tokenizer_name else model_args.model_name_or_path,
+        cache_dir=model_args.cache_dir,
+        use_fast=model_args.use_fast_tokenizer,
+        revision=model_args.model_revision,
+        use_auth_token=True if model_args.use_auth_token else None,
+    )
+    model = AutoModelForSpeechSeq2Seq.from_pretrained(
+        model_args.model_name_or_path,
+        config=config,
+        cache_dir=model_args.cache_dir,
+        revision=model_args.model_revision,
+        use_auth_token=True if model_args.use_auth_token else None,
+    )
+
+    if model.config.decoder_start_token_id is None:
+        raise ValueError("Make sure that `config.decoder_start_token_id` is correctly defined")
+
+    if model_args.freeze_feature_encoder:
+        model.freeze_feature_encoder()
+
+    if model_args.freeze_encoder:
+        model.freeze_encoder()
+
+    if data_args.language is not None:
+        # We only need to set the task id when the language is specified (i.e. in a multilingual setting)
+        tokenizer.set_prefix_tokens(language=data_args.language, task=data_args.task)
+
+    # 6. Resample speech dataset if necessary
+    dataset_sampling_rate = next(iter(raw_datasets.values())).features[data_args.audio_column_name].sampling_rate
+    if dataset_sampling_rate != feature_extractor.sampling_rate:
+        raw_datasets = raw_datasets.cast_column(
+            data_args.audio_column_name, datasets.features.Audio(sampling_rate=feature_extractor.sampling_rate)
+        )
+
+    # 7. Preprocessing the datasets.
+    # We need to read the audio files as arrays and tokenize the targets.
+    max_input_length = data_args.max_duration_in_seconds * feature_extractor.sampling_rate
+    min_input_length = data_args.min_duration_in_seconds * feature_extractor.sampling_rate
+    audio_column_name = data_args.audio_column_name
+    text_column_name = data_args.text_column_name
+    model_input_name = feature_extractor.model_input_names[0]
+    do_lower_case = data_args.do_lower_case
+    do_remove_punctuation = data_args.do_remove_punctuation
+    normalizer = BasicTextNormalizer()  # 'official' text normalizer from OpenAI
+
+    if data_args.max_train_samples is not None:
+        raw_datasets["train"] = (
+            raw_datasets["train"].take(data_args.max_train_samples)
+            if data_args.streaming
+            else raw_datasets["train"].select(range(data_args.max_train_samples))
+        )
+
+    if data_args.max_eval_samples is not None:
+        raw_datasets["eval"] = (
+            raw_datasets["eval"].take(data_args.max_eval_samples)
+            if data_args.streaming
+            else raw_datasets["eval"].select(range(data_args.max_eval_samples))
+        )
+
+    def prepare_dataset(batch):
+        # process audio
+        sample = batch[audio_column_name]
+        
+        # Handle different audio formats - some datasets provide raw arrays, others provide paths
+        if isinstance(sample, dict):
+            if "array" in sample:
+                audio_array = sample["array"]
+                sampling_rate = sample["sampling_rate"]
+            elif "path" in sample:
+                # Load from path if array is not available
+                audio_array = sample["path"]  # datasets will load the file for us
+                sampling_rate = sample.get("sampling_rate", feature_extractor.sampling_rate)
+            else:
+                raise ValueError(f"Unsupported audio format. Sample must contain either 'array' or 'path'. Got {sample.keys()}")
+        else:
+            # Assume it's a direct path or array
+            audio_array = sample
+            sampling_rate = feature_extractor.sampling_rate
+
+        inputs = feature_extractor(audio_array, sampling_rate=sampling_rate)
+        
+        # process audio length
+        if isinstance(audio_array, numpy.ndarray):
+            batch["input_length"] = len(audio_array)
+        else:
+            # If we couldn't get the direct array length, estimate it from the processed features
+            batch["input_length"] = inputs.get(model_input_name)[0].shape[0] * feature_extractor.hop_length
+
+        # process targets
+        input_str = batch[text_column_name].lower() if do_lower_case else batch[text_column_name]
+        if do_remove_punctuation:
+            input_str = normalizer(input_str).strip()
+        batch["labels"] = tokenizer(input_str).input_ids
+        return batch
+
+    with training_args.main_process_first(desc="dataset map pre-processing"):
+        vectorized_datasets = raw_datasets.map(
+            prepare_dataset,
+            remove_columns=raw_datasets_features,
+        ).with_format("torch")
+
+        if training_args.do_train and data_args.streaming:
+            # manually shuffle if streaming (done by the trainer for non-streaming)
+            vectorized_datasets["train"] = vectorized_datasets["train"].shuffle(
+                buffer_size=data_args.shuffle_buffer_size,
+                seed=training_args.seed,
+            )
+
+    # filter training data that is shorter than min_input_length or longer than
+    # max_input_length
+    def is_audio_in_length_range(length):
+        return min_input_length < length < max_input_length
+
+    if training_args.do_train:
+        vectorized_datasets["train"] = vectorized_datasets["train"].filter(
+            is_audio_in_length_range,
+            input_columns=["input_length"],
+        )
+
+    # 8. Load Metric
+    metric = evaluate.load("wer")
+    do_normalize_eval = data_args.do_normalize_eval
+
+    def compute_metrics(pred):
+        pred_ids = pred.predictions
+
+        pred.label_ids[pred.label_ids == -100] = tokenizer.pad_token_id
+
+        pred_str = tokenizer.batch_decode(pred_ids, skip_special_tokens=True)
+        # we do not want to group tokens when computing the metrics
+        label_str = tokenizer.batch_decode(pred.label_ids, skip_special_tokens=True)
+
+        if do_normalize_eval:
+            pred_str = [normalizer(pred) for pred in pred_str]
+            label_str = [normalizer(label) for label in label_str]
+            # filtering step to only evaluate the samples that correspond to non-zero references:
+            pred_str = [pred_str[i] for i in range(len(pred_str)) if len(label_str[i]) > 0]
+            label_str = [label_str[i] for i in range(len(label_str)) if len(label_str[i]) > 0]
+
+        wer = 100 * metric.compute(predictions=pred_str, references=label_str)
+
+        return {"wer": wer}
+
+    # 9. Create a single speech processor
+    if is_main_process(training_args.local_rank):
+        # save feature extractor, tokenizer and config
+        feature_extractor.save_pretrained(training_args.output_dir)
+        tokenizer.save_pretrained(training_args.output_dir)
+        config.save_pretrained(training_args.output_dir)
+
+    processor = AutoProcessor.from_pretrained(training_args.output_dir)
+
+    # 10. Define data collator
+    data_collator = DataCollatorSpeechSeq2SeqWithPadding(
+        processor=processor,
+        decoder_start_token_id=model.config.decoder_start_token_id,
+    )
+
+    # 11. Configure Trainer
+    # Trainer callback to reinitialise and reshuffle the streamable datasets at the beginning of each epoch
+    # Only required for streaming: Trainer automatically shuffles non-streaming datasets
+    class ShuffleCallback(TrainerCallback):
+        def on_train_begin(self, args, state, control, **kwargs):
+            self.trainer = kwargs.get('trainer')
+
+        def on_epoch_begin(self, args, state, control, **kwargs):
+            if not hasattr(self, "trainer") or not hasattr(self.trainer, "train_dataloader") or self.trainer.train_dataloader is None:
+                return
+            train_dataloader = self.trainer.train_dataloader
+            if isinstance(train_dataloader.dataset, IterableDatasetShard):
+                pass  # set_epoch() is handled by the Trainer
+            elif isinstance(train_dataloader.dataset, IterableDataset):
+                train_dataloader.dataset.set_epoch(train_dataloader.dataset._epoch + 1)
+
+    # Initialize Trainer
+    trainer = Seq2SeqTrainer(
+        model=model,
+        args=training_args,
+        train_dataset=vectorized_datasets["train"] if training_args.do_train else None,
+        eval_dataset=vectorized_datasets["eval"] if training_args.do_eval else None,
+        processing_class=feature_extractor,
+        data_collator=data_collator,
+        compute_metrics=compute_metrics if training_args.predict_with_generate else None,
+        callbacks=[ShuffleCallback()] if data_args.streaming else None,
+    )
+
+    # 12. Training
+    if training_args.do_train:
+        checkpoint = None
+        if training_args.resume_from_checkpoint is not None:
+            checkpoint = training_args.resume_from_checkpoint
+        elif last_checkpoint is not None:
+            checkpoint = last_checkpoint
+        train_result = trainer.train(resume_from_checkpoint=checkpoint)
+        trainer.save_model()  # Saves the feature extractor too for easy upload
+
+        metrics = train_result.metrics
+        if data_args.max_train_samples:
+            metrics["train_samples"] = data_args.max_train_samples
+        trainer.log_metrics("train", metrics)
+        trainer.save_metrics("train", metrics)
+        trainer.save_state()
+
+    # 13. Evaluation
+    results = {}
+    if training_args.do_eval:
+        logger.info("*** Evaluate ***")
+        metrics = trainer.evaluate(
+            metric_key_prefix="eval",
+            max_length=training_args.generation_max_length,
+            num_beams=training_args.generation_num_beams,
+        )
+        if data_args.max_eval_samples:
+            metrics["eval_samples"] = data_args.max_eval_samples
+
+        trainer.log_metrics("eval", metrics)
+        trainer.save_metrics("eval", metrics)
+
+    # 14. Write Training Stats
+    kwargs = {
+        "finetuned_from": model_args.model_name_or_path,
+        "tasks": "automatic-speech-recognition",
+        "tags": "whisper-event",
+    }
+    if data_args.dataset_name is not None:
+        kwargs["dataset_tags"] = data_args.dataset_name
+        if data_args.dataset_config_name is not None:
+            kwargs["dataset"] = f"{data_args.dataset_name} {data_args.dataset_config_name}"
+        else:
+            kwargs["dataset"] = data_args.dataset_name
+        if "common_voice" in data_args.dataset_name:
+            kwargs["language"] = data_args.dataset_config_name.split('-')[0]
+        if model_args.model_index_name is not None:
+            kwargs["model_name"] = model_args.model_index_name
+
+    if training_args.push_to_hub:
+        trainer.push_to_hub(**kwargs)
+    else:
+        trainer.create_model_card(**kwargs)
+
+    return results
+
+
+if __name__ == "__main__":
+    main()

tokenizer_config.json

@@ -12980,6 +12980,7 @@
   "clean_up_tokenization_spaces": true,
   "eos_token": "<|endoftext|>",
   "errors": "replace",
+  "extra_special_tokens": {},
   "model_max_length": 1024,
   "pad_token": "<|endoftext|>",
   "processor_class": "WhisperProcessor",

training_args.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:1e5015f6997af49dd4702cbba394870a18c74f3b62b5a4ffcc8bf3aa71cc41ee
-size 5368
+oid sha256:37d41e6c93c9164dab27b25a4957996293e07bbed9895811c22360ffbda7ebbf
+size 5432

wandb/debug-internal.log

@@ -0,0 +1,7 @@
+{"time":"2025-02-12T15:27:10.115999744Z","level":"INFO","msg":"stream: starting","core version":"0.19.6","symlink path":"/home/tknika/xezpeleta/whisper/whisper-small-eu/wandb/run-20250212_152709-lejyafmi/logs/debug-core.log"}
+{"time":"2025-02-12T15:27:10.219975741Z","level":"INFO","msg":"created new stream","id":"lejyafmi"}
+{"time":"2025-02-12T15:27:10.220016671Z","level":"INFO","msg":"stream: started","id":"lejyafmi"}
+{"time":"2025-02-12T15:27:10.220140679Z","level":"INFO","msg":"writer: Do: started","stream_id":"lejyafmi"}
+{"time":"2025-02-12T15:27:10.220197299Z","level":"INFO","msg":"handler: started","stream_id":"lejyafmi"}
+{"time":"2025-02-12T15:27:10.220285178Z","level":"INFO","msg":"sender: started","stream_id":"lejyafmi"}
+{"time":"2025-02-12T15:27:10.587185852Z","level":"INFO","msg":"Starting system monitor"}

wandb/debug.log

@@ -0,0 +1,25 @@
+2025-02-12 15:27:09,901 INFO    MainThread:243546 [wandb_setup.py:_flush():68] Current SDK version is 0.19.6
+2025-02-12 15:27:09,901 INFO    MainThread:243546 [wandb_setup.py:_flush():68] Configure stats pid to 243546
+2025-02-12 15:27:09,901 INFO    MainThread:243546 [wandb_setup.py:_flush():68] Loading settings from /home/tknika/.config/wandb/settings
+2025-02-12 15:27:09,901 INFO    MainThread:243546 [wandb_setup.py:_flush():68] Loading settings from /home/tknika/xezpeleta/whisper/whisper-small-eu/wandb/settings
+2025-02-12 15:27:09,901 INFO    MainThread:243546 [wandb_setup.py:_flush():68] Loading settings from environment variables
+2025-02-12 15:27:09,901 INFO    MainThread:243546 [wandb_init.py:setup_run_log_directory():637] Logging user logs to /home/tknika/xezpeleta/whisper/whisper-small-eu/wandb/run-20250212_152709-lejyafmi/logs/debug.log
+2025-02-12 15:27:09,901 INFO    MainThread:243546 [wandb_init.py:setup_run_log_directory():638] Logging internal logs to /home/tknika/xezpeleta/whisper/whisper-small-eu/wandb/run-20250212_152709-lejyafmi/logs/debug-internal.log
+2025-02-12 15:27:09,901 INFO    MainThread:243546 [wandb_init.py:init():756] calling init triggers
+2025-02-12 15:27:09,901 INFO    MainThread:243546 [wandb_init.py:init():761] wandb.init called with sweep_config: {}
+config: {'_wandb': {}}
+2025-02-12 15:27:09,901 INFO    MainThread:243546 [wandb_init.py:init():789] starting backend
+2025-02-12 15:27:10,107 INFO    MainThread:243546 [wandb_init.py:init():793] sending inform_init request
+2025-02-12 15:27:10,112 INFO    MainThread:243546 [backend.py:_multiprocessing_setup():97] multiprocessing start_methods=fork,spawn,forkserver, using: spawn
+2025-02-12 15:27:10,113 INFO    MainThread:243546 [wandb_init.py:init():808] backend started and connected
+2025-02-12 15:27:10,115 INFO    MainThread:243546 [wandb_init.py:init():901] updated telemetry
+2025-02-12 15:27:10,122 INFO    MainThread:243546 [wandb_init.py:init():936] communicating run to backend with 90.0 second timeout
+2025-02-12 15:27:10,584 INFO    MainThread:243546 [wandb_init.py:init():994] starting run threads in backend
+2025-02-12 15:27:10,691 INFO    MainThread:243546 [wandb_run.py:_console_start():2385] atexit reg
+2025-02-12 15:27:10,692 INFO    MainThread:243546 [wandb_run.py:_redirect():2235] redirect: wrap_raw
+2025-02-12 15:27:10,692 INFO    MainThread:243546 [wandb_run.py:_redirect():2300] Wrapping output streams.
+2025-02-12 15:27:10,692 INFO    MainThread:243546 [wandb_run.py:_redirect():2325] Redirects installed.
+2025-02-12 15:27:10,694 INFO    MainThread:243546 [wandb_init.py:init():1036] run started, returning control to user process
+2025-02-12 15:27:10,698 INFO    MainThread:243546 [wandb_run.py:_config_callback():1253] config_cb None None {'vocab_size': 51865, 'num_mel_bins': 80, 'd_model': 768, 'encoder_layers': 12, 'encoder_attention_heads': 12, 'decoder_layers': 12, 'decoder_attention_heads': 12, 'decoder_ffn_dim': 3072, 'encoder_ffn_dim': 3072, 'dropout': 0.0, 'attention_dropout': 0.0, 'activation_dropout': 0.0, 'activation_function': 'gelu', 'init_std': 0.02, 'encoder_layerdrop': 0.0, 'decoder_layerdrop': 0.0, 'use_cache': False, 'num_hidden_layers': 12, 'scale_embedding': False, 'max_source_positions': 1500, 'max_target_positions': 448, 'classifier_proj_size': 256, 'use_weighted_layer_sum': False, 'apply_spec_augment': False, 'mask_time_prob': 0.05, 'mask_time_length': 10, 'mask_time_min_masks': 2, 'mask_feature_prob': 0.0, 'mask_feature_length': 10, 'mask_feature_min_masks': 0, 'median_filter_width': 7, 'return_dict': True, 'output_hidden_states': False, 'output_attentions': False, 'torchscript': False, 'torch_dtype': 'float32', 'use_bfloat16': False, 'tf_legacy_loss': False, 'pruned_heads': {}, 'tie_word_embeddings': True, 'chunk_size_feed_forward': 0, 'is_encoder_decoder': True, 'is_decoder': False, 'cross_attention_hidden_size': None, 'add_cross_attention': False, 'tie_encoder_decoder': False, 'max_length': 448, 'min_length': 0, 'do_sample': False, 'early_stopping': False, 'num_beams': 1, 'num_beam_groups': 1, 'diversity_penalty': 0.0, 'temperature': 1.0, 'top_k': 50, 'top_p': 1.0, 'typical_p': 1.0, 'repetition_penalty': 1.0, 'length_penalty': 1.0, 'no_repeat_ngram_size': 0, 'encoder_no_repeat_ngram_size': 0, 'bad_words_ids': None, 'num_return_sequences': 1, 'output_scores': False, 'return_dict_in_generate': False, 'forced_bos_token_id': None, 'forced_eos_token_id': None, 'remove_invalid_values': False, 'exponential_decay_length_penalty': None, 'suppress_tokens': None, 'begin_suppress_tokens': [220, 50257], 'architectures': ['WhisperForConditionalGeneration'], 'finetuning_task': None, 'id2label': {0: 'LABEL_0', 1: 'LABEL_1'}, 'label2id': {'LABEL_0': 0, 'LABEL_1': 1}, 'tokenizer_class': None, 'prefix': None, 'bos_token_id': 50257, 'pad_token_id': 50257, 'eos_token_id': 50257, 'sep_token_id': None, 'decoder_start_token_id': 50258, 'task_specific_params': None, 'problem_type': None, '_name_or_path': 'openai/whisper-small', '_attn_implementation_autoset': True, 'transformers_version': '4.49.0.dev0', 'forced_decoder_ids': None, 'model_type': 'whisper', 'output_dir': './', 'overwrite_output_dir': True, 'do_train': True, 'do_eval': True, 'do_predict': False, 'eval_strategy': 'steps', 'prediction_loss_only': False, 'per_device_train_batch_size': 32, 'per_device_eval_batch_size': 16, 'per_gpu_train_batch_size': None, 'per_gpu_eval_batch_size': None, 'gradient_accumulation_steps': 1, 'eval_accumulation_steps': None, 'eval_delay': 0, 'torch_empty_cache_steps': None, 'learning_rate': 1e-05, 'weight_decay': 0.0, 'adam_beta1': 0.9, 'adam_beta2': 0.999, 'adam_epsilon': 1e-08, 'max_grad_norm': 1.0, 'num_train_epochs': 3.0, 'max_steps': 8000, 'lr_scheduler_type': 'linear', 'lr_scheduler_kwargs': {}, 'warmup_ratio': 0.0, 'warmup_steps': 500, 'log_level': 'passive', 'log_level_replica': 'warning', 'log_on_each_node': True, 'logging_dir': './runs/Feb12_15-26-19_tknika', 'logging_strategy': 'steps', 'logging_first_step': False, 'logging_steps': 25, 'logging_nan_inf_filter': True, 'save_strategy': 'steps', 'save_steps': 1000, 'save_total_limit': None, 'save_safetensors': True, 'save_on_each_node': False, 'save_only_model': False, 'restore_callback_states_from_checkpoint': False, 'no_cuda': False, 'use_cpu': False, 'use_mps_device': False, 'seed': 42, 'data_seed': None, 'jit_mode_eval': False, 'use_ipex': False, 'bf16': False, 'fp16': True, 'fp16_opt_level': 'O1', 'half_precision_backend': 'auto', 'bf16_full_eval': False, 'fp16_full_eval': False, 'tf32': None, 'local_rank': 0, 'ddp_backend': None, 'tpu_num_cores': None, 'tpu_metrics_debug': False, 'debug': [], 'dataloader_drop_last': False, 'eval_steps': 1000, 'dataloader_num_workers': 0, 'dataloader_prefetch_factor': None, 'past_index': -1, 'run_name': 'whisper-small-eu', 'disable_tqdm': False, 'remove_unused_columns': True, 'label_names': None, 'load_best_model_at_end': True, 'metric_for_best_model': 'wer', 'greater_is_better': False, 'ignore_data_skip': False, 'fsdp': [], 'fsdp_min_num_params': 0, 'fsdp_config': {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}, 'fsdp_transformer_layer_cls_to_wrap': None, 'accelerator_config': {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}, 'deepspeed': None, 'label_smoothing_factor': 0.0, 'optim': 'adamw_torch', 'optim_args': None, 'adafactor': False, 'group_by_length': False, 'length_column_name': 'input_length', 'report_to': ['wandb'], 'ddp_find_unused_parameters': None, 'ddp_bucket_cap_mb': None, 'ddp_broadcast_buffers': None, 'dataloader_pin_memory': True, 'dataloader_persistent_workers': False, 'skip_memory_metrics': True, 'use_legacy_prediction_loop': False, 'push_to_hub': True, 'resume_from_checkpoint': None, 'hub_model_id': None, 'hub_strategy': 'every_save', 'hub_token': '<HUB_TOKEN>', 'hub_private_repo': None, 'hub_always_push': False, 'gradient_checkpointing': True, 'gradient_checkpointing_kwargs': None, 'include_inputs_for_metrics': False, 'include_for_metrics': [], 'eval_do_concat_batches': True, 'fp16_backend': 'auto', 'evaluation_strategy': 'steps', 'push_to_hub_model_id': None, 'push_to_hub_organization': None, 'push_to_hub_token': '<PUSH_TO_HUB_TOKEN>', 'mp_parameters': '', 'auto_find_batch_size': False, 'full_determinism': False, 'torchdynamo': None, 'ray_scope': 'last', 'ddp_timeout': 1800, 'torch_compile': False, 'torch_compile_backend': None, 'torch_compile_mode': None, 'dispatch_batches': None, 'split_batches': None, 'include_tokens_per_second': False, 'include_num_input_tokens_seen': False, 'neftune_noise_alpha': None, 'optim_target_modules': None, 'batch_eval_metrics': False, 'eval_on_start': False, 'use_liger_kernel': False, 'eval_use_gather_object': False, 'average_tokens_across_devices': False, 'sortish_sampler': False, 'predict_with_generate': True, 'generation_max_length': 225, 'generation_num_beams': None, 'generation_config': None}
+2025-02-12 15:27:10,704 INFO    MainThread:243546 [wandb_config.py:__setitem__():154] config set model/num_parameters = 241734912 - <bound method Run._config_callback of <wandb.sdk.wandb_run.Run object at 0x7eb0a4c1e180>>
+2025-02-12 15:27:10,704 INFO    MainThread:243546 [wandb_run.py:_config_callback():1253] config_cb model/num_parameters 241734912 None

wandb/run-20250212_121751-d4i88lzt/files/config.yaml

@@ -0,0 +1,512 @@
+_attn_implementation_autoset:
+    value: true
+_name_or_path:
+    value: openai/whisper-small
+_wandb:
+    value:
+        cli_version: 0.19.6
+        m:
+            - "1": train/global_step
+              "6":
+                - 3
+              "7": []
+        python_version: 3.12.3
+        t:
+            "1":
+                - 1
+                - 5
+                - 11
+                - 49
+                - 51
+                - 53
+                - 55
+                - 71
+                - 100
+            "2":
+                - 1
+                - 5
+                - 11
+                - 49
+                - 51
+                - 53
+                - 55
+                - 71
+                - 100
+            "3":
+                - 7
+                - 13
+                - 19
+                - 23
+                - 55
+                - 66
+            "4": 3.12.3
+            "5": 0.19.6
+            "6": 4.49.0.dev0
+            "8":
+                - 5
+            "9":
+                "1": transformers_trainer
+            "12": 0.19.6
+            "13": linux-x86_64
+accelerator_config:
+    value:
+        dispatch_batches: null
+        even_batches: true
+        gradient_accumulation_kwargs: null
+        non_blocking: false
+        split_batches: false
+        use_seedable_sampler: true
+activation_dropout:
+    value: 0
+activation_function:
+    value: gelu
+adafactor:
+    value: false
+adam_beta1:
+    value: 0.9
+adam_beta2:
+    value: 0.999
+adam_epsilon:
+    value: 1e-08
+add_cross_attention:
+    value: false
+apply_spec_augment:
+    value: false
+architectures:
+    value:
+        - WhisperForConditionalGeneration
+attention_dropout:
+    value: 0
+auto_find_batch_size:
+    value: false
+average_tokens_across_devices:
+    value: false
+bad_words_ids:
+    value: null
+batch_eval_metrics:
+    value: false
+begin_suppress_tokens:
+    value:
+        - 220
+        - 50257
+bf16:
+    value: false
+bf16_full_eval:
+    value: false
+bos_token_id:
+    value: 50257
+chunk_size_feed_forward:
+    value: 0
+classifier_proj_size:
+    value: 256
+cross_attention_hidden_size:
+    value: null
+d_model:
+    value: 768
+data_seed:
+    value: null
+dataloader_drop_last:
+    value: false
+dataloader_num_workers:
+    value: 0
+dataloader_persistent_workers:
+    value: false
+dataloader_pin_memory:
+    value: true
+dataloader_prefetch_factor:
+    value: null
+ddp_backend:
+    value: null
+ddp_broadcast_buffers:
+    value: null
+ddp_bucket_cap_mb:
+    value: null
+ddp_find_unused_parameters:
+    value: null
+ddp_timeout:
+    value: 1800
+debug:
+    value: []
+decoder_attention_heads:
+    value: 12
+decoder_ffn_dim:
+    value: 3072
+decoder_layerdrop:
+    value: 0
+decoder_layers:
+    value: 12
+decoder_start_token_id:
+    value: 50258
+deepspeed:
+    value: null
+disable_tqdm:
+    value: false
+dispatch_batches:
+    value: null
+diversity_penalty:
+    value: 0
+do_eval:
+    value: true
+do_predict:
+    value: false
+do_sample:
+    value: false
+do_train:
+    value: true
+dropout:
+    value: 0
+early_stopping:
+    value: false
+encoder_attention_heads:
+    value: 12
+encoder_ffn_dim:
+    value: 3072
+encoder_layerdrop:
+    value: 0
+encoder_layers:
+    value: 12
+encoder_no_repeat_ngram_size:
+    value: 0
+eos_token_id:
+    value: 50257
+eval_accumulation_steps:
+    value: null
+eval_delay:
+    value: 0
+eval_do_concat_batches:
+    value: true
+eval_on_start:
+    value: false
+eval_steps:
+    value: 1000
+eval_strategy:
+    value: steps
+eval_use_gather_object:
+    value: false
+evaluation_strategy:
+    value: steps
+exponential_decay_length_penalty:
+    value: null
+finetuning_task:
+    value: null
+forced_bos_token_id:
+    value: null
+forced_decoder_ids:
+    value: null
+forced_eos_token_id:
+    value: null
+fp16:
+    value: true
+fp16_backend:
+    value: auto
+fp16_full_eval:
+    value: false
+fp16_opt_level:
+    value: O1
+fsdp:
+    value: []
+fsdp_config:
+    value:
+        min_num_params: 0
+        xla: false
+        xla_fsdp_grad_ckpt: false
+        xla_fsdp_v2: false
+fsdp_min_num_params:
+    value: 0
+fsdp_transformer_layer_cls_to_wrap:
+    value: null
+full_determinism:
+    value: false
+generation_config:
+    value: null
+generation_max_length:
+    value: 225
+generation_num_beams:
+    value: null
+gradient_accumulation_steps:
+    value: 1
+gradient_checkpointing:
+    value: true
+gradient_checkpointing_kwargs:
+    value: null
+greater_is_better:
+    value: false
+group_by_length:
+    value: false
+half_precision_backend:
+    value: auto
+hub_always_push:
+    value: false
+hub_model_id:
+    value: null
+hub_private_repo:
+    value: null
+hub_strategy:
+    value: every_save
+hub_token:
+    value: <HUB_TOKEN>
+id2label:
+    value:
+        "0": LABEL_0
+        "1": LABEL_1
+ignore_data_skip:
+    value: false
+include_for_metrics:
+    value: []
+include_inputs_for_metrics:
+    value: false
+include_num_input_tokens_seen:
+    value: false
+include_tokens_per_second:
+    value: false
+init_std:
+    value: 0.02
+is_decoder:
+    value: false
+is_encoder_decoder:
+    value: true
+jit_mode_eval:
+    value: false
+label_names:
+    value: null
+label_smoothing_factor:
+    value: 0
+label2id:
+    value:
+        LABEL_0: 0
+        LABEL_1: 1
+learning_rate:
+    value: 1e-05
+length_column_name:
+    value: input_length
+length_penalty:
+    value: 1
+load_best_model_at_end:
+    value: true
+local_rank:
+    value: 0
+log_level:
+    value: passive
+log_level_replica:
+    value: warning
+log_on_each_node:
+    value: true
+logging_dir:
+    value: ./runs/Feb12_12-17-27_tknika
+logging_first_step:
+    value: false
+logging_nan_inf_filter:
+    value: true
+logging_steps:
+    value: 25
+logging_strategy:
+    value: steps
+lr_scheduler_type:
+    value: linear
+mask_feature_length:
+    value: 10
+mask_feature_min_masks:
+    value: 0
+mask_feature_prob:
+    value: 0
+mask_time_length:
+    value: 10
+mask_time_min_masks:
+    value: 2
+mask_time_prob:
+    value: 0.05
+max_grad_norm:
+    value: 1
+max_length:
+    value: 448
+max_source_positions:
+    value: 1500
+max_steps:
+    value: 8000
+max_target_positions:
+    value: 448
+median_filter_width:
+    value: 7
+metric_for_best_model:
+    value: wer
+min_length:
+    value: 0
+model/num_parameters:
+    value: 241734912
+model_type:
+    value: whisper
+mp_parameters:
+    value: ""
+neftune_noise_alpha:
+    value: null
+no_cuda:
+    value: false
+no_repeat_ngram_size:
+    value: 0
+num_beam_groups:
+    value: 1
+num_beams:
+    value: 1
+num_hidden_layers:
+    value: 12
+num_mel_bins:
+    value: 80
+num_return_sequences:
+    value: 1
+num_train_epochs:
+    value: 3
+optim:
+    value: adamw_torch
+optim_args:
+    value: null
+optim_target_modules:
+    value: null
+output_attentions:
+    value: false
+output_dir:
+    value: ./
+output_hidden_states:
+    value: false
+output_scores:
+    value: false
+overwrite_output_dir:
+    value: true
+pad_token_id:
+    value: 50257
+past_index:
+    value: -1
+per_device_eval_batch_size:
+    value: 16
+per_device_train_batch_size:
+    value: 32
+per_gpu_eval_batch_size:
+    value: null
+per_gpu_train_batch_size:
+    value: null
+predict_with_generate:
+    value: true
+prediction_loss_only:
+    value: false
+prefix:
+    value: null
+problem_type:
+    value: null
+push_to_hub:
+    value: true
+push_to_hub_model_id:
+    value: null
+push_to_hub_organization:
+    value: null
+push_to_hub_token:
+    value: <PUSH_TO_HUB_TOKEN>
+ray_scope:
+    value: last
+remove_invalid_values:
+    value: false
+remove_unused_columns:
+    value: true
+repetition_penalty:
+    value: 1
+report_to:
+    value:
+        - wandb
+restore_callback_states_from_checkpoint:
+    value: false
+resume_from_checkpoint:
+    value: null
+return_dict:
+    value: true
+return_dict_in_generate:
+    value: false
+run_name:
+    value: whisper-small-eu
+save_on_each_node:
+    value: false
+save_only_model:
+    value: false
+save_safetensors:
+    value: true
+save_steps:
+    value: 1000
+save_strategy:
+    value: steps
+save_total_limit:
+    value: null
+scale_embedding:
+    value: false
+seed:
+    value: 42
+sep_token_id:
+    value: null
+skip_memory_metrics:
+    value: true
+sortish_sampler:
+    value: false
+split_batches:
+    value: null
+suppress_tokens:
+    value: null
+task_specific_params:
+    value: null
+temperature:
+    value: 1
+tf_legacy_loss:
+    value: false
+tf32:
+    value: null
+tie_encoder_decoder:
+    value: false
+tie_word_embeddings:
+    value: true
+tokenizer_class:
+    value: null
+top_k:
+    value: 50
+top_p:
+    value: 1
+torch_compile:
+    value: false
+torch_compile_backend:
+    value: null
+torch_compile_mode:
+    value: null
+torch_dtype:
+    value: float32
+torch_empty_cache_steps:
+    value: null
+torchdynamo:
+    value: null
+torchscript:
+    value: false
+tpu_metrics_debug:
+    value: false
+tpu_num_cores:
+    value: null
+transformers_version:
+    value: 4.49.0.dev0
+typical_p:
+    value: 1
+use_bfloat16:
+    value: false
+use_cache:
+    value: false
+use_cpu:
+    value: false
+use_ipex:
+    value: false
+use_legacy_prediction_loop:
+    value: false
+use_liger_kernel:
+    value: false
+use_mps_device:
+    value: false
+use_weighted_layer_sum:
+    value: false
+vocab_size:
+    value: 51865
+warmup_ratio:
+    value: 0
+warmup_steps:
+    value: 500
+weight_decay:
+    value: 0

wandb/run-20250212_121751-d4i88lzt/files/output.log

@@ -0,0 +1,22 @@
+  0%|                                                                                                                                               | 0/8000 [00:00<?, ?it/s]Traceback (most recent call last):
+  File "/home/tknika/xezpeleta/whisper/whisper-small-eu/run_speech_recognition_seq2seq_streaming.py", line 630, in <module>
+    main()
+  File "/home/tknika/xezpeleta/whisper/whisper-small-eu/run_speech_recognition_seq2seq_streaming.py", line 579, in main
+    train_result = trainer.train(resume_from_checkpoint=checkpoint)
+                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/tknika/xezpeleta/whisper/whisper-small-eu/.venv/lib/python3.12/site-packages/transformers/trainer.py", line 2197, in train
+    return inner_training_loop(
+           ^^^^^^^^^^^^^^^^^^^^
+  File "/home/tknika/xezpeleta/whisper/whisper-small-eu/.venv/lib/python3.12/site-packages/transformers/trainer.py", line 2438, in _inner_training_loop
+    self.control = self.callback_handler.on_epoch_begin(args, self.state, self.control)
+                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/tknika/xezpeleta/whisper/whisper-small-eu/.venv/lib/python3.12/site-packages/transformers/trainer_callback.py", line 514, in on_epoch_begin
+    return self.call_event("on_epoch_begin", args, state, control)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/tknika/xezpeleta/whisper/whisper-small-eu/.venv/lib/python3.12/site-packages/transformers/trainer_callback.py", line 557, in call_event
+    result = getattr(callback, event)(
+             ^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/tknika/xezpeleta/whisper/whisper-small-eu/run_speech_recognition_seq2seq_streaming.py", line 555, in on_epoch_begin
+    if isinstance(train_dataloader.dataset, IterableDatasetShard):
+                  ^^^^^^^^^^^^^^^^^^^^^^^^
+AttributeError: 'NoneType' object has no attribute 'dataset'

wandb/run-20250212_121751-d4i88lzt/files/requirements.txt

@@ -0,0 +1,115 @@
+aiosignal==1.3.2
+Markdown==3.7
+more-itertools==10.6.0
+requests==2.32.3
+sentry-sdk==2.21.0
+torchaudio==2.6.0
+charset-normalizer==3.4.1
+docker-pycreds==0.4.0
+nvidia-cusolver-cu12==11.6.1.9
+PyYAML==6.0.2
+librosa==0.10.2.post1
+soxr==0.5.0.post1
+multiprocess==0.70.16
+setuptools==75.8.0
+nvidia-cufft-cu12==11.2.1.3
+joblib==1.4.2
+pytz==2025.1
+pip==24.0
+scikit-learn==1.6.1
+certifi==2025.1.31
+jiwer==3.1.0
+regex==2024.11.6
+annotated-types==0.7.0
+grpcio==1.70.0
+msgpack==1.1.0
+mpmath==1.3.0
+nvidia-cudnn-cu12==9.1.0.70
+soundfile==0.13.1
+dill==0.3.8
+nvidia-nvtx-cu12==12.4.127
+six==1.17.0
+nvidia-cuda-cupti-cu12==12.4.127
+pyarrow==19.0.0
+nvidia-nccl-cu12==2.21.5
+psutil==6.1.1
+decorator==5.1.1
+llvmlite==0.44.0
+frozenlist==1.5.0
+pydantic==2.10.6
+networkx==3.4.2
+idna==3.10
+wandb==0.19.6
+aiohttp==3.11.12
+RapidFuzz==3.12.1
+pandas==2.2.3
+python-dateutil==2.9.0.post0
+numpy==2.1.3
+tokenizers==0.21.0
+nvidia-cusparselt-cu12==0.6.2
+typing_extensions==4.12.2
+urllib3==2.3.0
+setproctitle==1.3.4
+tzdata==2025.1
+sympy==1.13.1
+pooch==1.8.2
+click==8.1.8
+pydantic_core==2.27.2
+MarkupSafe==3.0.2
+scipy==1.15.1
+accelerate==1.3.0
+tensorboard==2.19.0
+protobuf==5.29.3
+gitdb==4.0.12
+smmap==5.0.2
+absl-py==2.1.0
+tqdm==4.67.1
+yarl==1.18.3
+pycparser==2.22
+nvidia-cusparse-cu12==12.3.1.170
+attrs==25.1.0
+lazy_loader==0.4
+tensorboard-data-server==0.7.2
+threadpoolctl==3.5.0
+GitPython==3.1.44
+safetensors==0.5.2
+fsspec==2024.12.0
+nvidia-cuda-nvrtc-cu12==12.4.127
+filelock==3.17.0
+aiohappyeyeballs==2.4.6
+packaging==24.2
+datasets==3.2.1.dev0
+audioread==3.0.1
+propcache==0.2.1
+transformers==4.49.0.dev0
+nvidia-cuda-runtime-cu12==12.4.127
+cffi==1.17.1
+evaluate==0.4.3
+Werkzeug==3.1.3
+huggingface-hub==0.28.1
+Jinja2==3.1.5
+torch==2.6.0
+nvidia-curand-cu12==10.3.5.147
+xxhash==3.5.0
+platformdirs==4.3.6
+multidict==6.1.0
+nvidia-cublas-cu12==12.4.5.8
+nvidia-nvjitlink-cu12==12.4.127
+triton==3.2.0
+numba==0.61.0
+importlib_metadata==8.0.0
+platformdirs==4.2.2
+typeguard==4.3.0
+more-itertools==10.3.0
+tomli==2.0.1
+autocommand==2.2.2
+zipp==3.19.2
+typing_extensions==4.12.2
+backports.tarfile==1.2.0
+inflect==7.3.1
+jaraco.text==3.12.1
+wheel==0.43.0
+packaging==24.2
+jaraco.collections==5.1.0
+jaraco.functools==4.0.1
+jaraco.context==5.3.0

wandb/run-20250212_121751-d4i88lzt/files/wandb-metadata.json

@@ -0,0 +1,85 @@
+{
+  "os":  "Linux-6.8.0-48-generic-x86_64-with-glibc2.39",
+  "python":  "CPython 3.12.3",
+  "startedAt":  "2025-02-12T12:17:51.527114Z",
+  "args":  [
+    "--model_name_or_path=openai/whisper-small",
+    "--dataset_name=asierhv/composite_corpus_eu_v2.1",
+    "--language=basque",
+    "--train_split_name=train",
+    "--eval_split_name=dev_parl+test_parl+test_cv+test_oslr",
+    "--model_index_name=Whisper Small Basque",
+    "--max_steps=8000",
+    "--output_dir=./",
+    "--per_device_train_batch_size=32",
+    "--per_device_eval_batch_size=16",
+    "--gradient_accumulation_steps=1",
+    "--logging_steps=25",
+    "--learning_rate=1e-5",
+    "--warmup_steps=500",
+    "--evaluation_strategy=steps",
+    "--eval_steps=1000",
+    "--save_strategy=steps",
+    "--save_steps=1000",
+    "--generation_max_length=225",
+    "--length_column_name=input_length",
+    "--max_duration_in_seconds=30",
+    "--text_column_name=sentence",
+    "--freeze_feature_encoder=False",
+    "--report_to=tensorboard",
+    "--metric_for_best_model=wer",
+    "--greater_is_better=False",
+    "--load_best_model_at_end",
+    "--gradient_checkpointing",
+    "--fp16",
+    "--overwrite_output_dir",
+    "--do_train",
+    "--do_eval",
+    "--predict_with_generate",
+    "--do_normalize_eval",
+    "--streaming",
+    "--use_auth_token",
+    "--push_to_hub",
+    "--report_to",
+    "wandb",
+    "--run_name",
+    "whisper-small-eu"
+  ],
+  "program":  "/home/tknika/xezpeleta/whisper/whisper-small-eu/run_speech_recognition_seq2seq_streaming.py",
+  "codePath":  "run_speech_recognition_seq2seq_streaming.py",
+  "git":  {
+    "remote":  "https://huggingface.co/xezpeleta/whisper-small-eu",
+    "commit":  "9c975864b20b4df94398a870e97cad2934253ec3"
+  },
+  "email":  "xezpeleta@gmail.com",
+  "root":  "/home/tknika/xezpeleta/whisper/whisper-small-eu",
+  "host":  "tknika",
+  "executable":  "/home/tknika/xezpeleta/whisper/whisper-small-eu/.venv/bin/python",
+  "codePathLocal":  "run_speech_recognition_seq2seq_streaming.py",
+  "cpu_count":  8,
+  "cpu_count_logical":  8,
+  "gpu":  "NVIDIA L40-48Q",
+  "gpu_count":  1,
+  "disk":  {
+    "/":  {
+      "total":  "525987168256",
+      "used":  "297346564096"
+    }
+  },
+  "memory":  {
+    "total":  "33654022144"
+  },
+  "cpu":  {
+    "count":  8,
+    "countLogical":  8
+  },
+  "gpu_nvidia":  [
+    {
+      "name":  "NVIDIA L40-48Q",
+      "memoryTotal":  "51539607552",
+      "cudaCores":  18176,
+      "architecture":  "Ada"
+    }
+  ],
+  "cudaVersion":  "12.4"
+}

wandb/run-20250212_121751-d4i88lzt/files/wandb-summary.json

@@ -0,0 +1 @@
+{"_wandb":{"runtime":0}}

wandb/run-20250212_121751-d4i88lzt/logs/debug-core.log

@@ -0,0 +1,14 @@
+{"time":"2025-02-12T12:17:51.340771692Z","level":"INFO","msg":"main: starting server","port-filename":"/tmp/tmpu_kqxp5v/port-223392.txt","pid":223392,"log-level":0,"disable-analytics":false,"shutdown-on-parent-exit":false}
+{"time":"2025-02-12T12:17:51.391525122Z","level":"INFO","msg":"Will exit if parent process dies.","ppid":223392}
+{"time":"2025-02-12T12:17:51.391505422Z","level":"INFO","msg":"server is running","addr":{"IP":"127.0.0.1","Port":35377,"Zone":""}}
+{"time":"2025-02-12T12:17:51.521026758Z","level":"INFO","msg":"connection: ManageConnectionData: new connection created","id":"127.0.0.1:42852"}
+{"time":"2025-02-12T12:17:51.529437253Z","level":"INFO","msg":"handleInformInit: received","streamId":"d4i88lzt","id":"127.0.0.1:42852"}
+{"time":"2025-02-12T12:17:51.635683608Z","level":"INFO","msg":"handleInformInit: stream started","streamId":"d4i88lzt","id":"127.0.0.1:42852"}
+{"time":"2025-02-12T12:17:52.089736796Z","level":"INFO","msg":"handleInformTeardown: server teardown initiated","id":"127.0.0.1:42852"}
+{"time":"2025-02-12T12:17:52.089842845Z","level":"INFO","msg":"connection: closing","id":"127.0.0.1:42852"}
+{"time":"2025-02-12T12:17:52.089890025Z","level":"INFO","msg":"connection: closed successfully","id":"127.0.0.1:42852"}
+{"time":"2025-02-12T12:17:52.089878375Z","level":"INFO","msg":"server is shutting down"}
+{"time":"2025-02-12T12:17:52.241493374Z","level":"ERROR","msg":"processOutgoingData: flush error","error":"write tcp 127.0.0.1:35377->127.0.0.1:42852: use of closed network connection","id":"127.0.0.1:42852"}
+{"time":"2025-02-12T12:17:53.244042129Z","level":"INFO","msg":"handleInformTeardown: server shutdown complete","id":"127.0.0.1:42852"}
+{"time":"2025-02-12T12:17:53.244065929Z","level":"INFO","msg":"connection: ManageConnectionData: connection closed","id":"127.0.0.1:42852"}
+{"time":"2025-02-12T12:17:53.244128968Z","level":"INFO","msg":"server is closed"}

wandb/run-20250212_121751-d4i88lzt/logs/debug-internal.log

@@ -0,0 +1,15 @@
+{"time":"2025-02-12T12:17:51.5298133Z","level":"INFO","msg":"stream: starting","core version":"0.19.6","symlink path":"/home/tknika/xezpeleta/whisper/whisper-small-eu/wandb/run-20250212_121751-d4i88lzt/logs/debug-core.log"}
+{"time":"2025-02-12T12:17:51.635607299Z","level":"INFO","msg":"created new stream","id":"d4i88lzt"}
+{"time":"2025-02-12T12:17:51.635674098Z","level":"INFO","msg":"stream: started","id":"d4i88lzt"}
+{"time":"2025-02-12T12:17:51.635773898Z","level":"INFO","msg":"writer: Do: started","stream_id":"d4i88lzt"}
+{"time":"2025-02-12T12:17:51.635842217Z","level":"INFO","msg":"sender: started","stream_id":"d4i88lzt"}
+{"time":"2025-02-12T12:17:51.635963186Z","level":"INFO","msg":"handler: started","stream_id":"d4i88lzt"}
+{"time":"2025-02-12T12:17:51.947487454Z","level":"INFO","msg":"Starting system monitor"}
+{"time":"2025-02-12T12:17:52.089832235Z","level":"INFO","msg":"stream: closing","id":"d4i88lzt"}
+{"time":"2025-02-12T12:17:52.089860885Z","level":"INFO","msg":"Stopping system monitor"}
+{"time":"2025-02-12T12:17:52.090422051Z","level":"INFO","msg":"Stopped system monitor"}
+{"time":"2025-02-12T12:17:53.018559862Z","level":"INFO","msg":"fileTransfer: Close: file transfer manager closed"}
+{"time":"2025-02-12T12:17:53.24378817Z","level":"INFO","msg":"handler: closed","stream_id":"d4i88lzt"}
+{"time":"2025-02-12T12:17:53.24383994Z","level":"INFO","msg":"writer: Close: closed","stream_id":"d4i88lzt"}
+{"time":"2025-02-12T12:17:53.24386653Z","level":"INFO","msg":"sender: closed","stream_id":"d4i88lzt"}
+{"time":"2025-02-12T12:17:53.243926789Z","level":"INFO","msg":"stream: closed","id":"d4i88lzt"}

wandb/run-20250212_121751-d4i88lzt/logs/debug.log

@@ -0,0 +1,26 @@
+2025-02-12 12:17:51,311 INFO    MainThread:223392 [wandb_setup.py:_flush():68] Current SDK version is 0.19.6
+2025-02-12 12:17:51,311 INFO    MainThread:223392 [wandb_setup.py:_flush():68] Configure stats pid to 223392
+2025-02-12 12:17:51,311 INFO    MainThread:223392 [wandb_setup.py:_flush():68] Loading settings from /home/tknika/.config/wandb/settings
+2025-02-12 12:17:51,311 INFO    MainThread:223392 [wandb_setup.py:_flush():68] Loading settings from /home/tknika/xezpeleta/whisper/whisper-small-eu/wandb/settings
+2025-02-12 12:17:51,311 INFO    MainThread:223392 [wandb_setup.py:_flush():68] Loading settings from environment variables
+2025-02-12 12:17:51,311 INFO    MainThread:223392 [wandb_init.py:setup_run_log_directory():637] Logging user logs to /home/tknika/xezpeleta/whisper/whisper-small-eu/wandb/run-20250212_121751-d4i88lzt/logs/debug.log
+2025-02-12 12:17:51,311 INFO    MainThread:223392 [wandb_init.py:setup_run_log_directory():638] Logging internal logs to /home/tknika/xezpeleta/whisper/whisper-small-eu/wandb/run-20250212_121751-d4i88lzt/logs/debug-internal.log
+2025-02-12 12:17:51,311 INFO    MainThread:223392 [wandb_init.py:init():756] calling init triggers
+2025-02-12 12:17:51,312 INFO    MainThread:223392 [wandb_init.py:init():761] wandb.init called with sweep_config: {}
+config: {'_wandb': {}}
+2025-02-12 12:17:51,312 INFO    MainThread:223392 [wandb_init.py:init():789] starting backend
+2025-02-12 12:17:51,521 INFO    MainThread:223392 [wandb_init.py:init():793] sending inform_init request
+2025-02-12 12:17:51,526 INFO    MainThread:223392 [backend.py:_multiprocessing_setup():97] multiprocessing start_methods=fork,spawn,forkserver, using: spawn
+2025-02-12 12:17:51,526 INFO    MainThread:223392 [wandb_init.py:init():808] backend started and connected
+2025-02-12 12:17:51,528 INFO    MainThread:223392 [wandb_init.py:init():901] updated telemetry
+2025-02-12 12:17:51,535 INFO    MainThread:223392 [wandb_init.py:init():936] communicating run to backend with 90.0 second timeout
+2025-02-12 12:17:51,944 INFO    MainThread:223392 [wandb_init.py:init():994] starting run threads in backend
+2025-02-12 12:17:52,049 INFO    MainThread:223392 [wandb_run.py:_console_start():2385] atexit reg
+2025-02-12 12:17:52,049 INFO    MainThread:223392 [wandb_run.py:_redirect():2235] redirect: wrap_raw
+2025-02-12 12:17:52,049 INFO    MainThread:223392 [wandb_run.py:_redirect():2300] Wrapping output streams.
+2025-02-12 12:17:52,049 INFO    MainThread:223392 [wandb_run.py:_redirect():2325] Redirects installed.
+2025-02-12 12:17:52,051 INFO    MainThread:223392 [wandb_init.py:init():1036] run started, returning control to user process
+2025-02-12 12:17:52,052 INFO    MainThread:223392 [wandb_run.py:_config_callback():1253] config_cb None None {'vocab_size': 51865, 'num_mel_bins': 80, 'd_model': 768, 'encoder_layers': 12, 'encoder_attention_heads': 12, 'decoder_layers': 12, 'decoder_attention_heads': 12, 'decoder_ffn_dim': 3072, 'encoder_ffn_dim': 3072, 'dropout': 0.0, 'attention_dropout': 0.0, 'activation_dropout': 0.0, 'activation_function': 'gelu', 'init_std': 0.02, 'encoder_layerdrop': 0.0, 'decoder_layerdrop': 0.0, 'use_cache': False, 'num_hidden_layers': 12, 'scale_embedding': False, 'max_source_positions': 1500, 'max_target_positions': 448, 'classifier_proj_size': 256, 'use_weighted_layer_sum': False, 'apply_spec_augment': False, 'mask_time_prob': 0.05, 'mask_time_length': 10, 'mask_time_min_masks': 2, 'mask_feature_prob': 0.0, 'mask_feature_length': 10, 'mask_feature_min_masks': 0, 'median_filter_width': 7, 'return_dict': True, 'output_hidden_states': False, 'output_attentions': False, 'torchscript': False, 'torch_dtype': 'float32', 'use_bfloat16': False, 'tf_legacy_loss': False, 'pruned_heads': {}, 'tie_word_embeddings': True, 'chunk_size_feed_forward': 0, 'is_encoder_decoder': True, 'is_decoder': False, 'cross_attention_hidden_size': None, 'add_cross_attention': False, 'tie_encoder_decoder': False, 'max_length': 448, 'min_length': 0, 'do_sample': False, 'early_stopping': False, 'num_beams': 1, 'num_beam_groups': 1, 'diversity_penalty': 0.0, 'temperature': 1.0, 'top_k': 50, 'top_p': 1.0, 'typical_p': 1.0, 'repetition_penalty': 1.0, 'length_penalty': 1.0, 'no_repeat_ngram_size': 0, 'encoder_no_repeat_ngram_size': 0, 'bad_words_ids': None, 'num_return_sequences': 1, 'output_scores': False, 'return_dict_in_generate': False, 'forced_bos_token_id': None, 'forced_eos_token_id': None, 'remove_invalid_values': False, 'exponential_decay_length_penalty': None, 'suppress_tokens': None, 'begin_suppress_tokens': [220, 50257], 'architectures': ['WhisperForConditionalGeneration'], 'finetuning_task': None, 'id2label': {0: 'LABEL_0', 1: 'LABEL_1'}, 'label2id': {'LABEL_0': 0, 'LABEL_1': 1}, 'tokenizer_class': None, 'prefix': None, 'bos_token_id': 50257, 'pad_token_id': 50257, 'eos_token_id': 50257, 'sep_token_id': None, 'decoder_start_token_id': 50258, 'task_specific_params': None, 'problem_type': None, '_name_or_path': 'openai/whisper-small', '_attn_implementation_autoset': True, 'transformers_version': '4.49.0.dev0', 'forced_decoder_ids': None, 'model_type': 'whisper', 'output_dir': './', 'overwrite_output_dir': True, 'do_train': True, 'do_eval': True, 'do_predict': False, 'eval_strategy': 'steps', 'prediction_loss_only': False, 'per_device_train_batch_size': 32, 'per_device_eval_batch_size': 16, 'per_gpu_train_batch_size': None, 'per_gpu_eval_batch_size': None, 'gradient_accumulation_steps': 1, 'eval_accumulation_steps': None, 'eval_delay': 0, 'torch_empty_cache_steps': None, 'learning_rate': 1e-05, 'weight_decay': 0.0, 'adam_beta1': 0.9, 'adam_beta2': 0.999, 'adam_epsilon': 1e-08, 'max_grad_norm': 1.0, 'num_train_epochs': 3.0, 'max_steps': 8000, 'lr_scheduler_type': 'linear', 'lr_scheduler_kwargs': {}, 'warmup_ratio': 0.0, 'warmup_steps': 500, 'log_level': 'passive', 'log_level_replica': 'warning', 'log_on_each_node': True, 'logging_dir': './runs/Feb12_12-17-27_tknika', 'logging_strategy': 'steps', 'logging_first_step': False, 'logging_steps': 25, 'logging_nan_inf_filter': True, 'save_strategy': 'steps', 'save_steps': 1000, 'save_total_limit': None, 'save_safetensors': True, 'save_on_each_node': False, 'save_only_model': False, 'restore_callback_states_from_checkpoint': False, 'no_cuda': False, 'use_cpu': False, 'use_mps_device': False, 'seed': 42, 'data_seed': None, 'jit_mode_eval': False, 'use_ipex': False, 'bf16': False, 'fp16': True, 'fp16_opt_level': 'O1', 'half_precision_backend': 'auto', 'bf16_full_eval': False, 'fp16_full_eval': False, 'tf32': None, 'local_rank': 0, 'ddp_backend': None, 'tpu_num_cores': None, 'tpu_metrics_debug': False, 'debug': [], 'dataloader_drop_last': False, 'eval_steps': 1000, 'dataloader_num_workers': 0, 'dataloader_prefetch_factor': None, 'past_index': -1, 'run_name': 'whisper-small-eu', 'disable_tqdm': False, 'remove_unused_columns': True, 'label_names': None, 'load_best_model_at_end': True, 'metric_for_best_model': 'wer', 'greater_is_better': False, 'ignore_data_skip': False, 'fsdp': [], 'fsdp_min_num_params': 0, 'fsdp_config': {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}, 'fsdp_transformer_layer_cls_to_wrap': None, 'accelerator_config': {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}, 'deepspeed': None, 'label_smoothing_factor': 0.0, 'optim': 'adamw_torch', 'optim_args': None, 'adafactor': False, 'group_by_length': False, 'length_column_name': 'input_length', 'report_to': ['wandb'], 'ddp_find_unused_parameters': None, 'ddp_bucket_cap_mb': None, 'ddp_broadcast_buffers': None, 'dataloader_pin_memory': True, 'dataloader_persistent_workers': False, 'skip_memory_metrics': True, 'use_legacy_prediction_loop': False, 'push_to_hub': True, 'resume_from_checkpoint': None, 'hub_model_id': None, 'hub_strategy': 'every_save', 'hub_token': '<HUB_TOKEN>', 'hub_private_repo': None, 'hub_always_push': False, 'gradient_checkpointing': True, 'gradient_checkpointing_kwargs': None, 'include_inputs_for_metrics': False, 'include_for_metrics': [], 'eval_do_concat_batches': True, 'fp16_backend': 'auto', 'evaluation_strategy': 'steps', 'push_to_hub_model_id': None, 'push_to_hub_organization': None, 'push_to_hub_token': '<PUSH_TO_HUB_TOKEN>', 'mp_parameters': '', 'auto_find_batch_size': False, 'full_determinism': False, 'torchdynamo': None, 'ray_scope': 'last', 'ddp_timeout': 1800, 'torch_compile': False, 'torch_compile_backend': None, 'torch_compile_mode': None, 'dispatch_batches': None, 'split_batches': None, 'include_tokens_per_second': False, 'include_num_input_tokens_seen': False, 'neftune_noise_alpha': None, 'optim_target_modules': None, 'batch_eval_metrics': False, 'eval_on_start': False, 'use_liger_kernel': False, 'eval_use_gather_object': False, 'average_tokens_across_devices': False, 'sortish_sampler': False, 'predict_with_generate': True, 'generation_max_length': 225, 'generation_num_beams': None, 'generation_config': None}
+2025-02-12 12:17:52,054 INFO    MainThread:223392 [wandb_config.py:__setitem__():154] config set model/num_parameters = 241734912 - <bound method Run._config_callback of <wandb.sdk.wandb_run.Run object at 0x75ef87e92c00>>
+2025-02-12 12:17:52,055 INFO    MainThread:223392 [wandb_run.py:_config_callback():1253] config_cb model/num_parameters 241734912 None
+2025-02-12 12:17:52,089 WARNING MsgRouterThr:223392 [router.py:message_loop():75] message_loop has been closed

wandb/run-20250212_122637-v3d3ouvn/files/config.yaml

@@ -0,0 +1,512 @@
+_attn_implementation_autoset:
+    value: true
+_name_or_path:
+    value: openai/whisper-small
+_wandb:
+    value:
+        cli_version: 0.19.6
+        m:
+            - "1": train/global_step
+              "6":
+                - 3
+              "7": []
+        python_version: 3.12.3
+        t:
+            "1":
+                - 1
+                - 5
+                - 11
+                - 49
+                - 51
+                - 53
+                - 55
+                - 71
+                - 100
+            "2":
+                - 1
+                - 5
+                - 11
+                - 49
+                - 51
+                - 53
+                - 55
+                - 71
+                - 100
+            "3":
+                - 7
+                - 13
+                - 19
+                - 23
+                - 55
+                - 66
+            "4": 3.12.3
+            "5": 0.19.6
+            "6": 4.49.0.dev0
+            "8":
+                - 5
+            "9":
+                "1": transformers_trainer
+            "12": 0.19.6
+            "13": linux-x86_64
+accelerator_config:
+    value:
+        dispatch_batches: null
+        even_batches: true
+        gradient_accumulation_kwargs: null
+        non_blocking: false
+        split_batches: false
+        use_seedable_sampler: true
+activation_dropout:
+    value: 0
+activation_function:
+    value: gelu
+adafactor:
+    value: false
+adam_beta1:
+    value: 0.9
+adam_beta2:
+    value: 0.999
+adam_epsilon:
+    value: 1e-08
+add_cross_attention:
+    value: false
+apply_spec_augment:
+    value: false
+architectures:
+    value:
+        - WhisperForConditionalGeneration
+attention_dropout:
+    value: 0
+auto_find_batch_size:
+    value: false
+average_tokens_across_devices:
+    value: false
+bad_words_ids:
+    value: null
+batch_eval_metrics:
+    value: false
+begin_suppress_tokens:
+    value:
+        - 220
+        - 50257
+bf16:
+    value: false
+bf16_full_eval:
+    value: false
+bos_token_id:
+    value: 50257
+chunk_size_feed_forward:
+    value: 0
+classifier_proj_size:
+    value: 256
+cross_attention_hidden_size:
+    value: null
+d_model:
+    value: 768
+data_seed:
+    value: null
+dataloader_drop_last:
+    value: false
+dataloader_num_workers:
+    value: 0
+dataloader_persistent_workers:
+    value: false
+dataloader_pin_memory:
+    value: true
+dataloader_prefetch_factor:
+    value: null
+ddp_backend:
+    value: null
+ddp_broadcast_buffers:
+    value: null
+ddp_bucket_cap_mb:
+    value: null
+ddp_find_unused_parameters:
+    value: null
+ddp_timeout:
+    value: 1800
+debug:
+    value: []
+decoder_attention_heads:
+    value: 12
+decoder_ffn_dim:
+    value: 3072
+decoder_layerdrop:
+    value: 0
+decoder_layers:
+    value: 12
+decoder_start_token_id:
+    value: 50258
+deepspeed:
+    value: null
+disable_tqdm:
+    value: false
+dispatch_batches:
+    value: null
+diversity_penalty:
+    value: 0
+do_eval:
+    value: true
+do_predict:
+    value: false
+do_sample:
+    value: false
+do_train:
+    value: true
+dropout:
+    value: 0
+early_stopping:
+    value: false
+encoder_attention_heads:
+    value: 12
+encoder_ffn_dim:
+    value: 3072
+encoder_layerdrop:
+    value: 0
+encoder_layers:
+    value: 12
+encoder_no_repeat_ngram_size:
+    value: 0
+eos_token_id:
+    value: 50257
+eval_accumulation_steps:
+    value: null
+eval_delay:
+    value: 0
+eval_do_concat_batches:
+    value: true
+eval_on_start:
+    value: false
+eval_steps:
+    value: 1000
+eval_strategy:
+    value: steps
+eval_use_gather_object:
+    value: false
+evaluation_strategy:
+    value: steps
+exponential_decay_length_penalty:
+    value: null
+finetuning_task:
+    value: null
+forced_bos_token_id:
+    value: null
+forced_decoder_ids:
+    value: null
+forced_eos_token_id:
+    value: null
+fp16:
+    value: true
+fp16_backend:
+    value: auto
+fp16_full_eval:
+    value: false
+fp16_opt_level:
+    value: O1
+fsdp:
+    value: []
+fsdp_config:
+    value:
+        min_num_params: 0
+        xla: false
+        xla_fsdp_grad_ckpt: false
+        xla_fsdp_v2: false
+fsdp_min_num_params:
+    value: 0
+fsdp_transformer_layer_cls_to_wrap:
+    value: null
+full_determinism:
+    value: false
+generation_config:
+    value: null
+generation_max_length:
+    value: 225
+generation_num_beams:
+    value: null
+gradient_accumulation_steps:
+    value: 1
+gradient_checkpointing:
+    value: true
+gradient_checkpointing_kwargs:
+    value: null
+greater_is_better:
+    value: false
+group_by_length:
+    value: false
+half_precision_backend:
+    value: auto
+hub_always_push:
+    value: false
+hub_model_id:
+    value: null
+hub_private_repo:
+    value: null
+hub_strategy:
+    value: every_save
+hub_token:
+    value: <HUB_TOKEN>
+id2label:
+    value:
+        "0": LABEL_0
+        "1": LABEL_1
+ignore_data_skip:
+    value: false
+include_for_metrics:
+    value: []
+include_inputs_for_metrics:
+    value: false
+include_num_input_tokens_seen:
+    value: false
+include_tokens_per_second:
+    value: false
+init_std:
+    value: 0.02
+is_decoder:
+    value: false
+is_encoder_decoder:
+    value: true
+jit_mode_eval:
+    value: false
+label_names:
+    value: null
+label_smoothing_factor:
+    value: 0
+label2id:
+    value:
+        LABEL_0: 0
+        LABEL_1: 1
+learning_rate:
+    value: 1e-05
+length_column_name:
+    value: input_length
+length_penalty:
+    value: 1
+load_best_model_at_end:
+    value: true
+local_rank:
+    value: 0
+log_level:
+    value: passive
+log_level_replica:
+    value: warning
+log_on_each_node:
+    value: true
+logging_dir:
+    value: ./runs/Feb12_12-26-11_tknika
+logging_first_step:
+    value: false
+logging_nan_inf_filter:
+    value: true
+logging_steps:
+    value: 25
+logging_strategy:
+    value: steps
+lr_scheduler_type:
+    value: linear
+mask_feature_length:
+    value: 10
+mask_feature_min_masks:
+    value: 0
+mask_feature_prob:
+    value: 0
+mask_time_length:
+    value: 10
+mask_time_min_masks:
+    value: 2
+mask_time_prob:
+    value: 0.05
+max_grad_norm:
+    value: 1
+max_length:
+    value: 448
+max_source_positions:
+    value: 1500
+max_steps:
+    value: 8000
+max_target_positions:
+    value: 448
+median_filter_width:
+    value: 7
+metric_for_best_model:
+    value: wer
+min_length:
+    value: 0
+model/num_parameters:
+    value: 241734912
+model_type:
+    value: whisper
+mp_parameters:
+    value: ""
+neftune_noise_alpha:
+    value: null
+no_cuda:
+    value: false
+no_repeat_ngram_size:
+    value: 0
+num_beam_groups:
+    value: 1
+num_beams:
+    value: 1
+num_hidden_layers:
+    value: 12
+num_mel_bins:
+    value: 80
+num_return_sequences:
+    value: 1
+num_train_epochs:
+    value: 3
+optim:
+    value: adamw_torch
+optim_args:
+    value: null
+optim_target_modules:
+    value: null
+output_attentions:
+    value: false
+output_dir:
+    value: ./
+output_hidden_states:
+    value: false
+output_scores:
+    value: false
+overwrite_output_dir:
+    value: true
+pad_token_id:
+    value: 50257
+past_index:
+    value: -1
+per_device_eval_batch_size:
+    value: 16
+per_device_train_batch_size:
+    value: 32
+per_gpu_eval_batch_size:
+    value: null
+per_gpu_train_batch_size:
+    value: null
+predict_with_generate:
+    value: true
+prediction_loss_only:
+    value: false
+prefix:
+    value: null
+problem_type:
+    value: null
+push_to_hub:
+    value: true
+push_to_hub_model_id:
+    value: null
+push_to_hub_organization:
+    value: null
+push_to_hub_token:
+    value: <PUSH_TO_HUB_TOKEN>
+ray_scope:
+    value: last
+remove_invalid_values:
+    value: false
+remove_unused_columns:
+    value: true
+repetition_penalty:
+    value: 1
+report_to:
+    value:
+        - wandb
+restore_callback_states_from_checkpoint:
+    value: false
+resume_from_checkpoint:
+    value: null
+return_dict:
+    value: true
+return_dict_in_generate:
+    value: false
+run_name:
+    value: whisper-small-eu
+save_on_each_node:
+    value: false
+save_only_model:
+    value: false
+save_safetensors:
+    value: true
+save_steps:
+    value: 1000
+save_strategy:
+    value: steps
+save_total_limit:
+    value: null
+scale_embedding:
+    value: false
+seed:
+    value: 42
+sep_token_id:
+    value: null
+skip_memory_metrics:
+    value: true
+sortish_sampler:
+    value: false
+split_batches:
+    value: null
+suppress_tokens:
+    value: null
+task_specific_params:
+    value: null
+temperature:
+    value: 1
+tf_legacy_loss:
+    value: false
+tf32:
+    value: null
+tie_encoder_decoder:
+    value: false
+tie_word_embeddings:
+    value: true
+tokenizer_class:
+    value: null
+top_k:
+    value: 50
+top_p:
+    value: 1
+torch_compile:
+    value: false
+torch_compile_backend:
+    value: null
+torch_compile_mode:
+    value: null
+torch_dtype:
+    value: float32
+torch_empty_cache_steps:
+    value: null
+torchdynamo:
+    value: null
+torchscript:
+    value: false
+tpu_metrics_debug:
+    value: false
+tpu_num_cores:
+    value: null
+transformers_version:
+    value: 4.49.0.dev0
+typical_p:
+    value: 1
+use_bfloat16:
+    value: false
+use_cache:
+    value: false
+use_cpu:
+    value: false
+use_ipex:
+    value: false
+use_legacy_prediction_loop:
+    value: false
+use_liger_kernel:
+    value: false
+use_mps_device:
+    value: false
+use_weighted_layer_sum:
+    value: false
+vocab_size:
+    value: 51865
+warmup_ratio:
+    value: 0
+warmup_steps:
+    value: 500
+weight_decay:
+    value: 0

wandb/run-20250212_122637-v3d3ouvn/files/output.log

@@ -0,0 +1,22 @@
+  0%|                                                                                                                                               | 0/8000 [00:00<?, ?it/s]Traceback (most recent call last):
+  File "/home/tknika/xezpeleta/whisper/whisper-small-eu/run_speech_recognition_seq2seq_streaming.py", line 630, in <module>
+    main()
+  File "/home/tknika/xezpeleta/whisper/whisper-small-eu/run_speech_recognition_seq2seq_streaming.py", line 579, in main
+    train_result = trainer.train(resume_from_checkpoint=checkpoint)
+                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/tknika/xezpeleta/whisper/whisper-small-eu/.venv/lib/python3.12/site-packages/transformers/trainer.py", line 2197, in train
+    return inner_training_loop(
+           ^^^^^^^^^^^^^^^^^^^^
+  File "/home/tknika/xezpeleta/whisper/whisper-small-eu/.venv/lib/python3.12/site-packages/transformers/trainer.py", line 2438, in _inner_training_loop
+    self.control = self.callback_handler.on_epoch_begin(args, self.state, self.control)
+                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/tknika/xezpeleta/whisper/whisper-small-eu/.venv/lib/python3.12/site-packages/transformers/trainer_callback.py", line 514, in on_epoch_begin
+    return self.call_event("on_epoch_begin", args, state, control)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/tknika/xezpeleta/whisper/whisper-small-eu/.venv/lib/python3.12/site-packages/transformers/trainer_callback.py", line 557, in call_event
+    result = getattr(callback, event)(
+             ^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/tknika/xezpeleta/whisper/whisper-small-eu/run_speech_recognition_seq2seq_streaming.py", line 555, in on_epoch_begin
+    if isinstance(train_dataloader.dataset, IterableDatasetShard):
+                  ^^^^^^^^^^^^^^^^^^^^^^^^
+AttributeError: 'NoneType' object has no attribute 'dataset'

wandb/run-20250212_122637-v3d3ouvn/files/requirements.txt

@@ -0,0 +1,115 @@
+aiosignal==1.3.2
+Markdown==3.7
+more-itertools==10.6.0
+requests==2.32.3
+sentry-sdk==2.21.0
+torchaudio==2.6.0
+charset-normalizer==3.4.1
+docker-pycreds==0.4.0
+nvidia-cusolver-cu12==11.6.1.9
+PyYAML==6.0.2
+librosa==0.10.2.post1
+soxr==0.5.0.post1
+multiprocess==0.70.16
+setuptools==75.8.0
+nvidia-cufft-cu12==11.2.1.3
+joblib==1.4.2
+pytz==2025.1
+pip==24.0
+scikit-learn==1.6.1
+certifi==2025.1.31
+jiwer==3.1.0
+regex==2024.11.6
+annotated-types==0.7.0
+grpcio==1.70.0
+msgpack==1.1.0
+mpmath==1.3.0
+nvidia-cudnn-cu12==9.1.0.70
+soundfile==0.13.1
+dill==0.3.8
+nvidia-nvtx-cu12==12.4.127
+six==1.17.0
+nvidia-cuda-cupti-cu12==12.4.127
+pyarrow==19.0.0
+nvidia-nccl-cu12==2.21.5
+psutil==6.1.1
+decorator==5.1.1
+llvmlite==0.44.0
+frozenlist==1.5.0
+pydantic==2.10.6
+networkx==3.4.2
+idna==3.10
+wandb==0.19.6
+aiohttp==3.11.12
+RapidFuzz==3.12.1
+pandas==2.2.3
+python-dateutil==2.9.0.post0
+numpy==2.1.3
+tokenizers==0.21.0
+nvidia-cusparselt-cu12==0.6.2
+typing_extensions==4.12.2
+urllib3==2.3.0
+setproctitle==1.3.4
+tzdata==2025.1
+sympy==1.13.1
+pooch==1.8.2
+click==8.1.8
+pydantic_core==2.27.2
+MarkupSafe==3.0.2
+scipy==1.15.1
+accelerate==1.3.0
+tensorboard==2.19.0
+protobuf==5.29.3
+gitdb==4.0.12
+smmap==5.0.2
+absl-py==2.1.0
+tqdm==4.67.1
+yarl==1.18.3
+pycparser==2.22
+nvidia-cusparse-cu12==12.3.1.170
+attrs==25.1.0
+lazy_loader==0.4
+tensorboard-data-server==0.7.2
+threadpoolctl==3.5.0
+GitPython==3.1.44
+safetensors==0.5.2
+fsspec==2024.12.0
+nvidia-cuda-nvrtc-cu12==12.4.127
+filelock==3.17.0
+aiohappyeyeballs==2.4.6
+packaging==24.2
+datasets==3.2.1.dev0
+audioread==3.0.1
+propcache==0.2.1
+transformers==4.49.0.dev0
+nvidia-cuda-runtime-cu12==12.4.127
+cffi==1.17.1
+evaluate==0.4.3
+Werkzeug==3.1.3
+huggingface-hub==0.28.1
+Jinja2==3.1.5
+torch==2.6.0
+nvidia-curand-cu12==10.3.5.147
+xxhash==3.5.0
+platformdirs==4.3.6
+multidict==6.1.0
+nvidia-cublas-cu12==12.4.5.8
+nvidia-nvjitlink-cu12==12.4.127
+triton==3.2.0
+numba==0.61.0
+importlib_metadata==8.0.0
+platformdirs==4.2.2
+typeguard==4.3.0
+more-itertools==10.3.0
+tomli==2.0.1
+autocommand==2.2.2
+zipp==3.19.2
+typing_extensions==4.12.2
+backports.tarfile==1.2.0
+inflect==7.3.1
+jaraco.text==3.12.1
+wheel==0.43.0
+packaging==24.2
+jaraco.collections==5.1.0
+jaraco.functools==4.0.1
+jaraco.context==5.3.0

wandb/run-20250212_122637-v3d3ouvn/files/wandb-metadata.json

@@ -0,0 +1,85 @@
+{
+  "os":  "Linux-6.8.0-48-generic-x86_64-with-glibc2.39",
+  "python":  "CPython 3.12.3",
+  "startedAt":  "2025-02-12T12:26:37.277902Z",
+  "args":  [
+    "--model_name_or_path=openai/whisper-small",
+    "--dataset_name=asierhv/composite_corpus_eu_v2.1",
+    "--language=basque",
+    "--train_split_name=train",
+    "--eval_split_name=dev_parl+test_parl+test_cv+test_oslr",
+    "--model_index_name=Whisper Small Basque",
+    "--max_steps=8000",
+    "--output_dir=./",
+    "--per_device_train_batch_size=32",
+    "--per_device_eval_batch_size=16",
+    "--gradient_accumulation_steps=1",
+    "--logging_steps=25",
+    "--learning_rate=1e-5",
+    "--warmup_steps=500",
+    "--evaluation_strategy=steps",
+    "--eval_steps=1000",
+    "--save_strategy=steps",
+    "--save_steps=1000",
+    "--generation_max_length=225",
+    "--length_column_name=input_length",
+    "--max_duration_in_seconds=30",
+    "--text_column_name=sentence",
+    "--freeze_feature_encoder=False",
+    "--report_to=tensorboard",
+    "--metric_for_best_model=wer",
+    "--greater_is_better=False",
+    "--load_best_model_at_end",
+    "--gradient_checkpointing",
+    "--fp16",
+    "--overwrite_output_dir",
+    "--do_train",
+    "--do_eval",
+    "--predict_with_generate",
+    "--do_normalize_eval",
+    "--streaming",
+    "--use_auth_token",
+    "--push_to_hub",
+    "--report_to",
+    "wandb",
+    "--run_name",
+    "whisper-small-eu"
+  ],
+  "program":  "/home/tknika/xezpeleta/whisper/whisper-small-eu/run_speech_recognition_seq2seq_streaming.py",
+  "codePath":  "run_speech_recognition_seq2seq_streaming.py",
+  "git":  {
+    "remote":  "https://huggingface.co/xezpeleta/whisper-small-eu",
+    "commit":  "9c975864b20b4df94398a870e97cad2934253ec3"
+  },
+  "email":  "xezpeleta@gmail.com",
+  "root":  "/home/tknika/xezpeleta/whisper/whisper-small-eu",
+  "host":  "tknika",
+  "executable":  "/home/tknika/xezpeleta/whisper/whisper-small-eu/.venv/bin/python",
+  "codePathLocal":  "run_speech_recognition_seq2seq_streaming.py",
+  "cpu_count":  8,
+  "cpu_count_logical":  8,
+  "gpu":  "NVIDIA L40-48Q",
+  "gpu_count":  1,
+  "disk":  {
+    "/":  {
+      "total":  "525987168256",
+      "used":  "297346666496"
+    }
+  },
+  "memory":  {
+    "total":  "33654022144"
+  },
+  "cpu":  {
+    "count":  8,
+    "countLogical":  8
+  },
+  "gpu_nvidia":  [
+    {
+      "name":  "NVIDIA L40-48Q",
+      "memoryTotal":  "51539607552",
+      "cudaCores":  18176,
+      "architecture":  "Ada"
+    }
+  ],
+  "cudaVersion":  "12.4"
+}

wandb/run-20250212_122637-v3d3ouvn/files/wandb-summary.json

@@ -0,0 +1 @@
+{"_wandb":{"runtime":0}}

wandb/run-20250212_122637-v3d3ouvn/logs/debug-core.log

@@ -0,0 +1,14 @@
+{"time":"2025-02-12T12:26:37.096402413Z","level":"INFO","msg":"main: starting server","port-filename":"/tmp/tmpcjtnmyy4/port-224110.txt","pid":224110,"log-level":0,"disable-analytics":false,"shutdown-on-parent-exit":false}
+{"time":"2025-02-12T12:26:37.136235603Z","level":"INFO","msg":"Will exit if parent process dies.","ppid":224110}
+{"time":"2025-02-12T12:26:37.136202753Z","level":"INFO","msg":"server is running","addr":{"IP":"127.0.0.1","Port":34237,"Zone":""}}
+{"time":"2025-02-12T12:26:37.272154204Z","level":"INFO","msg":"connection: ManageConnectionData: new connection created","id":"127.0.0.1:48156"}
+{"time":"2025-02-12T12:26:37.280104802Z","level":"INFO","msg":"handleInformInit: received","streamId":"v3d3ouvn","id":"127.0.0.1:48156"}
+{"time":"2025-02-12T12:26:37.385176776Z","level":"INFO","msg":"handleInformInit: stream started","streamId":"v3d3ouvn","id":"127.0.0.1:48156"}
+{"time":"2025-02-12T12:26:37.805006529Z","level":"INFO","msg":"handleInformTeardown: server teardown initiated","id":"127.0.0.1:48156"}
+{"time":"2025-02-12T12:26:37.805113068Z","level":"INFO","msg":"server is shutting down"}
+{"time":"2025-02-12T12:26:37.805096358Z","level":"INFO","msg":"connection: closing","id":"127.0.0.1:48156"}
+{"time":"2025-02-12T12:26:37.805232397Z","level":"INFO","msg":"connection: closed successfully","id":"127.0.0.1:48156"}
+{"time":"2025-02-12T12:26:37.995286135Z","level":"ERROR","msg":"processOutgoingData: flush error","error":"write tcp 127.0.0.1:34237->127.0.0.1:48156: use of closed network connection","id":"127.0.0.1:48156"}
+{"time":"2025-02-12T12:26:39.120464204Z","level":"INFO","msg":"handleInformTeardown: server shutdown complete","id":"127.0.0.1:48156"}
+{"time":"2025-02-12T12:26:39.120492104Z","level":"INFO","msg":"connection: ManageConnectionData: connection closed","id":"127.0.0.1:48156"}
+{"time":"2025-02-12T12:26:39.120507034Z","level":"INFO","msg":"server is closed"}

wandb/run-20250212_122637-v3d3ouvn/logs/debug-internal.log

@@ -0,0 +1,15 @@
+{"time":"2025-02-12T12:26:37.280430379Z","level":"INFO","msg":"stream: starting","core version":"0.19.6","symlink path":"/home/tknika/xezpeleta/whisper/whisper-small-eu/wandb/run-20250212_122637-v3d3ouvn/logs/debug-core.log"}
+{"time":"2025-02-12T12:26:37.385120447Z","level":"INFO","msg":"created new stream","id":"v3d3ouvn"}
+{"time":"2025-02-12T12:26:37.385167976Z","level":"INFO","msg":"stream: started","id":"v3d3ouvn"}
+{"time":"2025-02-12T12:26:37.385225046Z","level":"INFO","msg":"writer: Do: started","stream_id":"v3d3ouvn"}
+{"time":"2025-02-12T12:26:37.385310785Z","level":"INFO","msg":"sender: started","stream_id":"v3d3ouvn"}
+{"time":"2025-02-12T12:26:37.385358905Z","level":"INFO","msg":"handler: started","stream_id":"v3d3ouvn"}
+{"time":"2025-02-12T12:26:37.656629021Z","level":"INFO","msg":"Starting system monitor"}
+{"time":"2025-02-12T12:26:37.805164318Z","level":"INFO","msg":"stream: closing","id":"v3d3ouvn"}
+{"time":"2025-02-12T12:26:37.805220128Z","level":"INFO","msg":"Stopping system monitor"}
+{"time":"2025-02-12T12:26:37.805952593Z","level":"INFO","msg":"Stopped system monitor"}
+{"time":"2025-02-12T12:26:38.904190518Z","level":"INFO","msg":"fileTransfer: Close: file transfer manager closed"}
+{"time":"2025-02-12T12:26:39.120209166Z","level":"INFO","msg":"handler: closed","stream_id":"v3d3ouvn"}
+{"time":"2025-02-12T12:26:39.120281046Z","level":"INFO","msg":"writer: Close: closed","stream_id":"v3d3ouvn"}
+{"time":"2025-02-12T12:26:39.120312915Z","level":"INFO","msg":"sender: closed","stream_id":"v3d3ouvn"}
+{"time":"2025-02-12T12:26:39.120355495Z","level":"INFO","msg":"stream: closed","id":"v3d3ouvn"}

wandb/run-20250212_122637-v3d3ouvn/logs/debug.log

@@ -0,0 +1,26 @@
+2025-02-12 12:26:37,062 INFO    MainThread:224110 [wandb_setup.py:_flush():68] Current SDK version is 0.19.6
+2025-02-12 12:26:37,062 INFO    MainThread:224110 [wandb_setup.py:_flush():68] Configure stats pid to 224110
+2025-02-12 12:26:37,062 INFO    MainThread:224110 [wandb_setup.py:_flush():68] Loading settings from /home/tknika/.config/wandb/settings
+2025-02-12 12:26:37,062 INFO    MainThread:224110 [wandb_setup.py:_flush():68] Loading settings from /home/tknika/xezpeleta/whisper/whisper-small-eu/wandb/settings
+2025-02-12 12:26:37,062 INFO    MainThread:224110 [wandb_setup.py:_flush():68] Loading settings from environment variables
+2025-02-12 12:26:37,062 INFO    MainThread:224110 [wandb_init.py:setup_run_log_directory():637] Logging user logs to /home/tknika/xezpeleta/whisper/whisper-small-eu/wandb/run-20250212_122637-v3d3ouvn/logs/debug.log
+2025-02-12 12:26:37,062 INFO    MainThread:224110 [wandb_init.py:setup_run_log_directory():638] Logging internal logs to /home/tknika/xezpeleta/whisper/whisper-small-eu/wandb/run-20250212_122637-v3d3ouvn/logs/debug-internal.log
+2025-02-12 12:26:37,062 INFO    MainThread:224110 [wandb_init.py:init():756] calling init triggers
+2025-02-12 12:26:37,062 INFO    MainThread:224110 [wandb_init.py:init():761] wandb.init called with sweep_config: {}
+config: {'_wandb': {}}
+2025-02-12 12:26:37,062 INFO    MainThread:224110 [wandb_init.py:init():789] starting backend
+2025-02-12 12:26:37,272 INFO    MainThread:224110 [wandb_init.py:init():793] sending inform_init request
+2025-02-12 12:26:37,277 INFO    MainThread:224110 [backend.py:_multiprocessing_setup():97] multiprocessing start_methods=fork,spawn,forkserver, using: spawn
+2025-02-12 12:26:37,277 INFO    MainThread:224110 [wandb_init.py:init():808] backend started and connected
+2025-02-12 12:26:37,279 INFO    MainThread:224110 [wandb_init.py:init():901] updated telemetry
+2025-02-12 12:26:37,285 INFO    MainThread:224110 [wandb_init.py:init():936] communicating run to backend with 90.0 second timeout
+2025-02-12 12:26:37,653 INFO    MainThread:224110 [wandb_init.py:init():994] starting run threads in backend
+2025-02-12 12:26:37,764 INFO    MainThread:224110 [wandb_run.py:_console_start():2385] atexit reg
+2025-02-12 12:26:37,765 INFO    MainThread:224110 [wandb_run.py:_redirect():2235] redirect: wrap_raw
+2025-02-12 12:26:37,765 INFO    MainThread:224110 [wandb_run.py:_redirect():2300] Wrapping output streams.
+2025-02-12 12:26:37,765 INFO    MainThread:224110 [wandb_run.py:_redirect():2325] Redirects installed.
+2025-02-12 12:26:37,766 INFO    MainThread:224110 [wandb_init.py:init():1036] run started, returning control to user process
+2025-02-12 12:26:37,767 INFO    MainThread:224110 [wandb_run.py:_config_callback():1253] config_cb None None {'vocab_size': 51865, 'num_mel_bins': 80, 'd_model': 768, 'encoder_layers': 12, 'encoder_attention_heads': 12, 'decoder_layers': 12, 'decoder_attention_heads': 12, 'decoder_ffn_dim': 3072, 'encoder_ffn_dim': 3072, 'dropout': 0.0, 'attention_dropout': 0.0, 'activation_dropout': 0.0, 'activation_function': 'gelu', 'init_std': 0.02, 'encoder_layerdrop': 0.0, 'decoder_layerdrop': 0.0, 'use_cache': False, 'num_hidden_layers': 12, 'scale_embedding': False, 'max_source_positions': 1500, 'max_target_positions': 448, 'classifier_proj_size': 256, 'use_weighted_layer_sum': False, 'apply_spec_augment': False, 'mask_time_prob': 0.05, 'mask_time_length': 10, 'mask_time_min_masks': 2, 'mask_feature_prob': 0.0, 'mask_feature_length': 10, 'mask_feature_min_masks': 0, 'median_filter_width': 7, 'return_dict': True, 'output_hidden_states': False, 'output_attentions': False, 'torchscript': False, 'torch_dtype': 'float32', 'use_bfloat16': False, 'tf_legacy_loss': False, 'pruned_heads': {}, 'tie_word_embeddings': True, 'chunk_size_feed_forward': 0, 'is_encoder_decoder': True, 'is_decoder': False, 'cross_attention_hidden_size': None, 'add_cross_attention': False, 'tie_encoder_decoder': False, 'max_length': 448, 'min_length': 0, 'do_sample': False, 'early_stopping': False, 'num_beams': 1, 'num_beam_groups': 1, 'diversity_penalty': 0.0, 'temperature': 1.0, 'top_k': 50, 'top_p': 1.0, 'typical_p': 1.0, 'repetition_penalty': 1.0, 'length_penalty': 1.0, 'no_repeat_ngram_size': 0, 'encoder_no_repeat_ngram_size': 0, 'bad_words_ids': None, 'num_return_sequences': 1, 'output_scores': False, 'return_dict_in_generate': False, 'forced_bos_token_id': None, 'forced_eos_token_id': None, 'remove_invalid_values': False, 'exponential_decay_length_penalty': None, 'suppress_tokens': None, 'begin_suppress_tokens': [220, 50257], 'architectures': ['WhisperForConditionalGeneration'], 'finetuning_task': None, 'id2label': {0: 'LABEL_0', 1: 'LABEL_1'}, 'label2id': {'LABEL_0': 0, 'LABEL_1': 1}, 'tokenizer_class': None, 'prefix': None, 'bos_token_id': 50257, 'pad_token_id': 50257, 'eos_token_id': 50257, 'sep_token_id': None, 'decoder_start_token_id': 50258, 'task_specific_params': None, 'problem_type': None, '_name_or_path': 'openai/whisper-small', '_attn_implementation_autoset': True, 'transformers_version': '4.49.0.dev0', 'forced_decoder_ids': None, 'model_type': 'whisper', 'output_dir': './', 'overwrite_output_dir': True, 'do_train': True, 'do_eval': True, 'do_predict': False, 'eval_strategy': 'steps', 'prediction_loss_only': False, 'per_device_train_batch_size': 32, 'per_device_eval_batch_size': 16, 'per_gpu_train_batch_size': None, 'per_gpu_eval_batch_size': None, 'gradient_accumulation_steps': 1, 'eval_accumulation_steps': None, 'eval_delay': 0, 'torch_empty_cache_steps': None, 'learning_rate': 1e-05, 'weight_decay': 0.0, 'adam_beta1': 0.9, 'adam_beta2': 0.999, 'adam_epsilon': 1e-08, 'max_grad_norm': 1.0, 'num_train_epochs': 3.0, 'max_steps': 8000, 'lr_scheduler_type': 'linear', 'lr_scheduler_kwargs': {}, 'warmup_ratio': 0.0, 'warmup_steps': 500, 'log_level': 'passive', 'log_level_replica': 'warning', 'log_on_each_node': True, 'logging_dir': './runs/Feb12_12-26-11_tknika', 'logging_strategy': 'steps', 'logging_first_step': False, 'logging_steps': 25, 'logging_nan_inf_filter': True, 'save_strategy': 'steps', 'save_steps': 1000, 'save_total_limit': None, 'save_safetensors': True, 'save_on_each_node': False, 'save_only_model': False, 'restore_callback_states_from_checkpoint': False, 'no_cuda': False, 'use_cpu': False, 'use_mps_device': False, 'seed': 42, 'data_seed': None, 'jit_mode_eval': False, 'use_ipex': False, 'bf16': False, 'fp16': True, 'fp16_opt_level': 'O1', 'half_precision_backend': 'auto', 'bf16_full_eval': False, 'fp16_full_eval': False, 'tf32': None, 'local_rank': 0, 'ddp_backend': None, 'tpu_num_cores': None, 'tpu_metrics_debug': False, 'debug': [], 'dataloader_drop_last': False, 'eval_steps': 1000, 'dataloader_num_workers': 0, 'dataloader_prefetch_factor': None, 'past_index': -1, 'run_name': 'whisper-small-eu', 'disable_tqdm': False, 'remove_unused_columns': True, 'label_names': None, 'load_best_model_at_end': True, 'metric_for_best_model': 'wer', 'greater_is_better': False, 'ignore_data_skip': False, 'fsdp': [], 'fsdp_min_num_params': 0, 'fsdp_config': {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}, 'fsdp_transformer_layer_cls_to_wrap': None, 'accelerator_config': {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}, 'deepspeed': None, 'label_smoothing_factor': 0.0, 'optim': 'adamw_torch', 'optim_args': None, 'adafactor': False, 'group_by_length': False, 'length_column_name': 'input_length', 'report_to': ['wandb'], 'ddp_find_unused_parameters': None, 'ddp_bucket_cap_mb': None, 'ddp_broadcast_buffers': None, 'dataloader_pin_memory': True, 'dataloader_persistent_workers': False, 'skip_memory_metrics': True, 'use_legacy_prediction_loop': False, 'push_to_hub': True, 'resume_from_checkpoint': None, 'hub_model_id': None, 'hub_strategy': 'every_save', 'hub_token': '<HUB_TOKEN>', 'hub_private_repo': None, 'hub_always_push': False, 'gradient_checkpointing': True, 'gradient_checkpointing_kwargs': None, 'include_inputs_for_metrics': False, 'include_for_metrics': [], 'eval_do_concat_batches': True, 'fp16_backend': 'auto', 'evaluation_strategy': 'steps', 'push_to_hub_model_id': None, 'push_to_hub_organization': None, 'push_to_hub_token': '<PUSH_TO_HUB_TOKEN>', 'mp_parameters': '', 'auto_find_batch_size': False, 'full_determinism': False, 'torchdynamo': None, 'ray_scope': 'last', 'ddp_timeout': 1800, 'torch_compile': False, 'torch_compile_backend': None, 'torch_compile_mode': None, 'dispatch_batches': None, 'split_batches': None, 'include_tokens_per_second': False, 'include_num_input_tokens_seen': False, 'neftune_noise_alpha': None, 'optim_target_modules': None, 'batch_eval_metrics': False, 'eval_on_start': False, 'use_liger_kernel': False, 'eval_use_gather_object': False, 'average_tokens_across_devices': False, 'sortish_sampler': False, 'predict_with_generate': True, 'generation_max_length': 225, 'generation_num_beams': None, 'generation_config': None}
+2025-02-12 12:26:37,770 INFO    MainThread:224110 [wandb_config.py:__setitem__():154] config set model/num_parameters = 241734912 - <bound method Run._config_callback of <wandb.sdk.wandb_run.Run object at 0x7a5cbc15a330>>
+2025-02-12 12:26:37,770 INFO    MainThread:224110 [wandb_run.py:_config_callback():1253] config_cb model/num_parameters 241734912 None
+2025-02-12 12:26:37,805 WARNING MsgRouterThr:224110 [router.py:message_loop():75] message_loop has been closed

wandb/run-20250212_122854-4m048f5s/files/config.yaml

@@ -0,0 +1,512 @@
+_attn_implementation_autoset:
+    value: true
+_name_or_path:
+    value: openai/whisper-small
+_wandb:
+    value:
+        cli_version: 0.19.6
+        m:
+            - "1": train/global_step
+              "6":
+                - 3
+              "7": []
+        python_version: 3.12.3
+        t:
+            "1":
+                - 1
+                - 5
+                - 11
+                - 49
+                - 51
+                - 53
+                - 55
+                - 71
+                - 100
+            "2":
+                - 1
+                - 5
+                - 11
+                - 49
+                - 51
+                - 53
+                - 55
+                - 71
+                - 100
+            "3":
+                - 7
+                - 13
+                - 19
+                - 23
+                - 55
+                - 66
+            "4": 3.12.3
+            "5": 0.19.6
+            "6": 4.49.0.dev0
+            "8":
+                - 5
+            "9":
+                "1": transformers_trainer
+            "12": 0.19.6
+            "13": linux-x86_64
+accelerator_config:
+    value:
+        dispatch_batches: null
+        even_batches: true
+        gradient_accumulation_kwargs: null
+        non_blocking: false
+        split_batches: false
+        use_seedable_sampler: true
+activation_dropout:
+    value: 0
+activation_function:
+    value: gelu
+adafactor:
+    value: false
+adam_beta1:
+    value: 0.9
+adam_beta2:
+    value: 0.999
+adam_epsilon:
+    value: 1e-08
+add_cross_attention:
+    value: false
+apply_spec_augment:
+    value: false
+architectures:
+    value:
+        - WhisperForConditionalGeneration
+attention_dropout:
+    value: 0
+auto_find_batch_size:
+    value: false
+average_tokens_across_devices:
+    value: false
+bad_words_ids:
+    value: null
+batch_eval_metrics:
+    value: false
+begin_suppress_tokens:
+    value:
+        - 220
+        - 50257
+bf16:
+    value: false
+bf16_full_eval:
+    value: false
+bos_token_id:
+    value: 50257
+chunk_size_feed_forward:
+    value: 0
+classifier_proj_size:
+    value: 256
+cross_attention_hidden_size:
+    value: null
+d_model:
+    value: 768
+data_seed:
+    value: null
+dataloader_drop_last:
+    value: false
+dataloader_num_workers:
+    value: 0
+dataloader_persistent_workers:
+    value: false
+dataloader_pin_memory:
+    value: true
+dataloader_prefetch_factor:
+    value: null
+ddp_backend:
+    value: null
+ddp_broadcast_buffers:
+    value: null
+ddp_bucket_cap_mb:
+    value: null
+ddp_find_unused_parameters:
+    value: null
+ddp_timeout:
+    value: 1800
+debug:
+    value: []
+decoder_attention_heads:
+    value: 12
+decoder_ffn_dim:
+    value: 3072
+decoder_layerdrop:
+    value: 0
+decoder_layers:
+    value: 12
+decoder_start_token_id:
+    value: 50258
+deepspeed:
+    value: null
+disable_tqdm:
+    value: false
+dispatch_batches:
+    value: null
+diversity_penalty:
+    value: 0
+do_eval:
+    value: true
+do_predict:
+    value: false
+do_sample:
+    value: false
+do_train:
+    value: true
+dropout:
+    value: 0
+early_stopping:
+    value: false
+encoder_attention_heads:
+    value: 12
+encoder_ffn_dim:
+    value: 3072
+encoder_layerdrop:
+    value: 0
+encoder_layers:
+    value: 12
+encoder_no_repeat_ngram_size:
+    value: 0
+eos_token_id:
+    value: 50257
+eval_accumulation_steps:
+    value: null
+eval_delay:
+    value: 0
+eval_do_concat_batches:
+    value: true
+eval_on_start:
+    value: false
+eval_steps:
+    value: 1000
+eval_strategy:
+    value: steps
+eval_use_gather_object:
+    value: false
+evaluation_strategy:
+    value: steps
+exponential_decay_length_penalty:
+    value: null
+finetuning_task:
+    value: null
+forced_bos_token_id:
+    value: null
+forced_decoder_ids:
+    value: null
+forced_eos_token_id:
+    value: null
+fp16:
+    value: true
+fp16_backend:
+    value: auto
+fp16_full_eval:
+    value: false
+fp16_opt_level:
+    value: O1
+fsdp:
+    value: []
+fsdp_config:
+    value:
+        min_num_params: 0
+        xla: false
+        xla_fsdp_grad_ckpt: false
+        xla_fsdp_v2: false
+fsdp_min_num_params:
+    value: 0
+fsdp_transformer_layer_cls_to_wrap:
+    value: null
+full_determinism:
+    value: false
+generation_config:
+    value: null
+generation_max_length:
+    value: 225
+generation_num_beams:
+    value: null
+gradient_accumulation_steps:
+    value: 1
+gradient_checkpointing:
+    value: true
+gradient_checkpointing_kwargs:
+    value: null
+greater_is_better:
+    value: false
+group_by_length:
+    value: false
+half_precision_backend:
+    value: auto
+hub_always_push:
+    value: false
+hub_model_id:
+    value: null
+hub_private_repo:
+    value: null
+hub_strategy:
+    value: every_save
+hub_token:
+    value: <HUB_TOKEN>
+id2label:
+    value:
+        "0": LABEL_0
+        "1": LABEL_1
+ignore_data_skip:
+    value: false
+include_for_metrics:
+    value: []
+include_inputs_for_metrics:
+    value: false
+include_num_input_tokens_seen:
+    value: false
+include_tokens_per_second:
+    value: false
+init_std:
+    value: 0.02
+is_decoder:
+    value: false
+is_encoder_decoder:
+    value: true
+jit_mode_eval:
+    value: false
+label_names:
+    value: null
+label_smoothing_factor:
+    value: 0
+label2id:
+    value:
+        LABEL_0: 0
+        LABEL_1: 1
+learning_rate:
+    value: 1e-05
+length_column_name:
+    value: input_length
+length_penalty:
+    value: 1
+load_best_model_at_end:
+    value: true
+local_rank:
+    value: 0
+log_level:
+    value: passive
+log_level_replica:
+    value: warning
+log_on_each_node:
+    value: true
+logging_dir:
+    value: ./runs/Feb12_12-28-29_tknika
+logging_first_step:
+    value: false
+logging_nan_inf_filter:
+    value: true
+logging_steps:
+    value: 25
+logging_strategy:
+    value: steps
+lr_scheduler_type:
+    value: linear
+mask_feature_length:
+    value: 10
+mask_feature_min_masks:
+    value: 0
+mask_feature_prob:
+    value: 0
+mask_time_length:
+    value: 10
+mask_time_min_masks:
+    value: 2
+mask_time_prob:
+    value: 0.05
+max_grad_norm:
+    value: 1
+max_length:
+    value: 448
+max_source_positions:
+    value: 1500
+max_steps:
+    value: 8000
+max_target_positions:
+    value: 448
+median_filter_width:
+    value: 7
+metric_for_best_model:
+    value: wer
+min_length:
+    value: 0
+model/num_parameters:
+    value: 241734912
+model_type:
+    value: whisper
+mp_parameters:
+    value: ""
+neftune_noise_alpha:
+    value: null
+no_cuda:
+    value: false
+no_repeat_ngram_size:
+    value: 0
+num_beam_groups:
+    value: 1
+num_beams:
+    value: 1
+num_hidden_layers:
+    value: 12
+num_mel_bins:
+    value: 80
+num_return_sequences:
+    value: 1
+num_train_epochs:
+    value: 3
+optim:
+    value: adamw_torch
+optim_args:
+    value: null
+optim_target_modules:
+    value: null
+output_attentions:
+    value: false
+output_dir:
+    value: ./
+output_hidden_states:
+    value: false
+output_scores:
+    value: false
+overwrite_output_dir:
+    value: true
+pad_token_id:
+    value: 50257
+past_index:
+    value: -1
+per_device_eval_batch_size:
+    value: 16
+per_device_train_batch_size:
+    value: 32
+per_gpu_eval_batch_size:
+    value: null
+per_gpu_train_batch_size:
+    value: null
+predict_with_generate:
+    value: true
+prediction_loss_only:
+    value: false
+prefix:
+    value: null
+problem_type:
+    value: null
+push_to_hub:
+    value: true
+push_to_hub_model_id:
+    value: null
+push_to_hub_organization:
+    value: null
+push_to_hub_token:
+    value: <PUSH_TO_HUB_TOKEN>
+ray_scope:
+    value: last
+remove_invalid_values:
+    value: false
+remove_unused_columns:
+    value: true
+repetition_penalty:
+    value: 1
+report_to:
+    value:
+        - wandb
+restore_callback_states_from_checkpoint:
+    value: false
+resume_from_checkpoint:
+    value: null
+return_dict:
+    value: true
+return_dict_in_generate:
+    value: false
+run_name:
+    value: whisper-small-eu
+save_on_each_node:
+    value: false
+save_only_model:
+    value: false
+save_safetensors:
+    value: true
+save_steps:
+    value: 1000
+save_strategy:
+    value: steps
+save_total_limit:
+    value: null
+scale_embedding:
+    value: false
+seed:
+    value: 42
+sep_token_id:
+    value: null
+skip_memory_metrics:
+    value: true
+sortish_sampler:
+    value: false
+split_batches:
+    value: null
+suppress_tokens:
+    value: null
+task_specific_params:
+    value: null
+temperature:
+    value: 1
+tf_legacy_loss:
+    value: false
+tf32:
+    value: null
+tie_encoder_decoder:
+    value: false
+tie_word_embeddings:
+    value: true
+tokenizer_class:
+    value: null
+top_k:
+    value: 50
+top_p:
+    value: 1
+torch_compile:
+    value: false
+torch_compile_backend:
+    value: null
+torch_compile_mode:
+    value: null
+torch_dtype:
+    value: float32
+torch_empty_cache_steps:
+    value: null
+torchdynamo:
+    value: null
+torchscript:
+    value: false
+tpu_metrics_debug:
+    value: false
+tpu_num_cores:
+    value: null
+transformers_version:
+    value: 4.49.0.dev0
+typical_p:
+    value: 1
+use_bfloat16:
+    value: false
+use_cache:
+    value: false
+use_cpu:
+    value: false
+use_ipex:
+    value: false
+use_legacy_prediction_loop:
+    value: false
+use_liger_kernel:
+    value: false
+use_mps_device:
+    value: false
+use_weighted_layer_sum:
+    value: false
+vocab_size:
+    value: 51865
+warmup_ratio:
+    value: 0
+warmup_steps:
+    value: 500
+weight_decay:
+    value: 0

wandb/run-20250212_122854-4m048f5s/files/output.log

@@ -0,0 +1,22 @@
+  0%|                                                                                                                                               | 0/8000 [00:00<?, ?it/s]Traceback (most recent call last):
+  File "/home/tknika/xezpeleta/whisper/whisper-small-eu/run_speech_recognition_seq2seq_streaming.py", line 630, in <module>
+    main()
+  File "/home/tknika/xezpeleta/whisper/whisper-small-eu/run_speech_recognition_seq2seq_streaming.py", line 579, in main
+    train_result = trainer.train(resume_from_checkpoint=checkpoint)
+                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/tknika/xezpeleta/whisper/whisper-small-eu/.venv/lib/python3.12/site-packages/transformers/trainer.py", line 2197, in train
+    return inner_training_loop(
+           ^^^^^^^^^^^^^^^^^^^^
+  File "/home/tknika/xezpeleta/whisper/whisper-small-eu/.venv/lib/python3.12/site-packages/transformers/trainer.py", line 2438, in _inner_training_loop
+    self.control = self.callback_handler.on_epoch_begin(args, self.state, self.control)
+                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/tknika/xezpeleta/whisper/whisper-small-eu/.venv/lib/python3.12/site-packages/transformers/trainer_callback.py", line 514, in on_epoch_begin
+    return self.call_event("on_epoch_begin", args, state, control)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/tknika/xezpeleta/whisper/whisper-small-eu/.venv/lib/python3.12/site-packages/transformers/trainer_callback.py", line 557, in call_event
+    result = getattr(callback, event)(
+             ^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/tknika/xezpeleta/whisper/whisper-small-eu/run_speech_recognition_seq2seq_streaming.py", line 555, in on_epoch_begin
+    if isinstance(train_dataloader.dataset, IterableDatasetShard):
+                  ^^^^^^^^^^^^^^^^^^^^^^^^
+AttributeError: 'NoneType' object has no attribute 'dataset'

wandb/run-20250212_122854-4m048f5s/files/requirements.txt

@@ -0,0 +1,115 @@
+aiosignal==1.3.2
+Markdown==3.7
+more-itertools==10.6.0
+requests==2.32.3
+sentry-sdk==2.21.0
+torchaudio==2.6.0
+charset-normalizer==3.4.1
+docker-pycreds==0.4.0
+nvidia-cusolver-cu12==11.6.1.9
+PyYAML==6.0.2
+librosa==0.10.2.post1
+soxr==0.5.0.post1
+multiprocess==0.70.16
+setuptools==75.8.0
+nvidia-cufft-cu12==11.2.1.3
+joblib==1.4.2
+pytz==2025.1
+pip==24.0
+scikit-learn==1.6.1
+certifi==2025.1.31
+jiwer==3.1.0
+regex==2024.11.6
+annotated-types==0.7.0
+grpcio==1.70.0
+msgpack==1.1.0
+mpmath==1.3.0
+nvidia-cudnn-cu12==9.1.0.70
+soundfile==0.13.1
+dill==0.3.8
+nvidia-nvtx-cu12==12.4.127
+six==1.17.0
+nvidia-cuda-cupti-cu12==12.4.127
+pyarrow==19.0.0
+nvidia-nccl-cu12==2.21.5
+psutil==6.1.1
+decorator==5.1.1
+llvmlite==0.44.0
+frozenlist==1.5.0
+pydantic==2.10.6
+networkx==3.4.2
+idna==3.10
+wandb==0.19.6
+aiohttp==3.11.12
+RapidFuzz==3.12.1
+pandas==2.2.3
+python-dateutil==2.9.0.post0
+numpy==2.1.3
+tokenizers==0.21.0
+nvidia-cusparselt-cu12==0.6.2
+typing_extensions==4.12.2
+urllib3==2.3.0
+setproctitle==1.3.4
+tzdata==2025.1
+sympy==1.13.1
+pooch==1.8.2
+click==8.1.8
+pydantic_core==2.27.2
+MarkupSafe==3.0.2
+scipy==1.15.1
+accelerate==1.3.0
+tensorboard==2.19.0
+protobuf==5.29.3
+gitdb==4.0.12
+smmap==5.0.2
+absl-py==2.1.0
+tqdm==4.67.1
+yarl==1.18.3
+pycparser==2.22
+nvidia-cusparse-cu12==12.3.1.170
+attrs==25.1.0
+lazy_loader==0.4
+tensorboard-data-server==0.7.2
+threadpoolctl==3.5.0
+GitPython==3.1.44
+safetensors==0.5.2
+fsspec==2024.12.0
+nvidia-cuda-nvrtc-cu12==12.4.127
+filelock==3.17.0
+aiohappyeyeballs==2.4.6
+packaging==24.2
+datasets==3.2.1.dev0
+audioread==3.0.1
+propcache==0.2.1
+transformers==4.49.0.dev0
+nvidia-cuda-runtime-cu12==12.4.127
+cffi==1.17.1
+evaluate==0.4.3
+Werkzeug==3.1.3
+huggingface-hub==0.28.1
+Jinja2==3.1.5
+torch==2.6.0
+nvidia-curand-cu12==10.3.5.147
+xxhash==3.5.0
+platformdirs==4.3.6
+multidict==6.1.0
+nvidia-cublas-cu12==12.4.5.8
+nvidia-nvjitlink-cu12==12.4.127
+triton==3.2.0
+numba==0.61.0
+importlib_metadata==8.0.0
+platformdirs==4.2.2
+typeguard==4.3.0
+more-itertools==10.3.0
+tomli==2.0.1
+autocommand==2.2.2
+zipp==3.19.2
+typing_extensions==4.12.2
+backports.tarfile==1.2.0
+inflect==7.3.1
+jaraco.text==3.12.1
+wheel==0.43.0
+packaging==24.2
+jaraco.collections==5.1.0
+jaraco.functools==4.0.1
+jaraco.context==5.3.0

wandb/run-20250212_122854-4m048f5s/files/wandb-metadata.json

@@ -0,0 +1,85 @@
+{
+  "os":  "Linux-6.8.0-48-generic-x86_64-with-glibc2.39",
+  "python":  "CPython 3.12.3",
+  "startedAt":  "2025-02-12T12:28:54.528397Z",
+  "args":  [
+    "--model_name_or_path=openai/whisper-small",
+    "--dataset_name=asierhv/composite_corpus_eu_v2.1",
+    "--language=basque",
+    "--train_split_name=train",
+    "--eval_split_name=dev_parl+test_parl+test_cv+test_oslr",
+    "--model_index_name=Whisper Small Basque",
+    "--max_steps=8000",
+    "--output_dir=./",
+    "--per_device_train_batch_size=32",
+    "--per_device_eval_batch_size=16",
+    "--gradient_accumulation_steps=1",
+    "--logging_steps=25",
+    "--learning_rate=1e-5",
+    "--warmup_steps=500",
+    "--evaluation_strategy=steps",
+    "--eval_steps=1000",
+    "--save_strategy=steps",
+    "--save_steps=1000",
+    "--generation_max_length=225",
+    "--length_column_name=input_length",
+    "--max_duration_in_seconds=30",
+    "--text_column_name=sentence",
+    "--freeze_feature_encoder=False",
+    "--report_to=tensorboard",
+    "--metric_for_best_model=wer",
+    "--greater_is_better=False",
+    "--load_best_model_at_end",
+    "--gradient_checkpointing",
+    "--fp16",
+    "--overwrite_output_dir",
+    "--do_train",
+    "--do_eval",
+    "--predict_with_generate",
+    "--do_normalize_eval",
+    "--streaming",
+    "--use_auth_token",
+    "--push_to_hub",
+    "--report_to",
+    "wandb",
+    "--run_name",
+    "whisper-small-eu"
+  ],
+  "program":  "/home/tknika/xezpeleta/whisper/whisper-small-eu/run_speech_recognition_seq2seq_streaming.py",
+  "codePath":  "run_speech_recognition_seq2seq_streaming.py",
+  "git":  {
+    "remote":  "https://huggingface.co/xezpeleta/whisper-small-eu",
+    "commit":  "9c975864b20b4df94398a870e97cad2934253ec3"
+  },
+  "email":  "xezpeleta@gmail.com",
+  "root":  "/home/tknika/xezpeleta/whisper/whisper-small-eu",
+  "host":  "tknika",
+  "executable":  "/home/tknika/xezpeleta/whisper/whisper-small-eu/.venv/bin/python",
+  "codePathLocal":  "run_speech_recognition_seq2seq_streaming.py",
+  "cpu_count":  8,
+  "cpu_count_logical":  8,
+  "gpu":  "NVIDIA L40-48Q",
+  "gpu_count":  1,
+  "disk":  {
+    "/":  {
+      "total":  "525987168256",
+      "used":  "297346756608"
+    }
+  },
+  "memory":  {
+    "total":  "33654022144"
+  },
+  "cpu":  {
+    "count":  8,
+    "countLogical":  8
+  },
+  "gpu_nvidia":  [
+    {
+      "name":  "NVIDIA L40-48Q",
+      "memoryTotal":  "51539607552",
+      "cudaCores":  18176,
+      "architecture":  "Ada"
+    }
+  ],
+  "cudaVersion":  "12.4"
+}

wandb/run-20250212_122854-4m048f5s/files/wandb-summary.json

@@ -0,0 +1 @@
+{"_wandb":{"runtime":0}}

wandb/run-20250212_122854-4m048f5s/logs/debug-core.log

@@ -0,0 +1,14 @@
+{"time":"2025-02-12T12:28:54.343223143Z","level":"INFO","msg":"main: starting server","port-filename":"/tmp/tmpmg8o5mqm/port-224528.txt","pid":224528,"log-level":0,"disable-analytics":false,"shutdown-on-parent-exit":false}
+{"time":"2025-02-12T12:28:54.34827505Z","level":"INFO","msg":"Will exit if parent process dies.","ppid":224528}
+{"time":"2025-02-12T12:28:54.34821581Z","level":"INFO","msg":"server is running","addr":{"IP":"127.0.0.1","Port":44981,"Zone":""}}
+{"time":"2025-02-12T12:28:54.521681286Z","level":"INFO","msg":"connection: ManageConnectionData: new connection created","id":"127.0.0.1:51116"}
+{"time":"2025-02-12T12:28:54.53173104Z","level":"INFO","msg":"handleInformInit: received","streamId":"4m048f5s","id":"127.0.0.1:51116"}
+{"time":"2025-02-12T12:28:54.636478984Z","level":"INFO","msg":"handleInformInit: stream started","streamId":"4m048f5s","id":"127.0.0.1:51116"}
+{"time":"2025-02-12T12:28:55.028718067Z","level":"INFO","msg":"handleInformTeardown: server teardown initiated","id":"127.0.0.1:51116"}
+{"time":"2025-02-12T12:28:55.028819337Z","level":"INFO","msg":"connection: closing","id":"127.0.0.1:51116"}
+{"time":"2025-02-12T12:28:55.028818347Z","level":"INFO","msg":"server is shutting down"}
+{"time":"2025-02-12T12:28:55.028912476Z","level":"INFO","msg":"connection: closed successfully","id":"127.0.0.1:51116"}
+{"time":"2025-02-12T12:28:55.368512133Z","level":"ERROR","msg":"processOutgoingData: flush error","error":"write tcp 127.0.0.1:44981->127.0.0.1:51116: use of closed network connection","id":"127.0.0.1:51116"}
+{"time":"2025-02-12T12:28:56.249016671Z","level":"INFO","msg":"handleInformTeardown: server shutdown complete","id":"127.0.0.1:51116"}
+{"time":"2025-02-12T12:28:56.249048031Z","level":"INFO","msg":"connection: ManageConnectionData: connection closed","id":"127.0.0.1:51116"}
+{"time":"2025-02-12T12:28:56.249109521Z","level":"INFO","msg":"server is closed"}

wandb/run-20250212_122854-4m048f5s/logs/debug-internal.log

@@ -0,0 +1,15 @@
+{"time":"2025-02-12T12:28:54.532033248Z","level":"INFO","msg":"stream: starting","core version":"0.19.6","symlink path":"/home/tknika/xezpeleta/whisper/whisper-small-eu/wandb/run-20250212_122854-4m048f5s/logs/debug-core.log"}
+{"time":"2025-02-12T12:28:54.636425775Z","level":"INFO","msg":"created new stream","id":"4m048f5s"}
+{"time":"2025-02-12T12:28:54.636473304Z","level":"INFO","msg":"stream: started","id":"4m048f5s"}
+{"time":"2025-02-12T12:28:54.636556744Z","level":"INFO","msg":"writer: Do: started","stream_id":"4m048f5s"}
+{"time":"2025-02-12T12:28:54.636597734Z","level":"INFO","msg":"handler: started","stream_id":"4m048f5s"}
+{"time":"2025-02-12T12:28:54.636670993Z","level":"INFO","msg":"sender: started","stream_id":"4m048f5s"}
+{"time":"2025-02-12T12:28:54.886030488Z","level":"INFO","msg":"Starting system monitor"}
+{"time":"2025-02-12T12:28:55.028853626Z","level":"INFO","msg":"stream: closing","id":"4m048f5s"}
+{"time":"2025-02-12T12:28:55.028891716Z","level":"INFO","msg":"Stopping system monitor"}
+{"time":"2025-02-12T12:28:55.029589382Z","level":"INFO","msg":"Stopped system monitor"}
+{"time":"2025-02-12T12:28:56.017176821Z","level":"INFO","msg":"fileTransfer: Close: file transfer manager closed"}
+{"time":"2025-02-12T12:28:56.248703933Z","level":"INFO","msg":"handler: closed","stream_id":"4m048f5s"}
+{"time":"2025-02-12T12:28:56.248768363Z","level":"INFO","msg":"writer: Close: closed","stream_id":"4m048f5s"}
+{"time":"2025-02-12T12:28:56.248802103Z","level":"INFO","msg":"sender: closed","stream_id":"4m048f5s"}
+{"time":"2025-02-12T12:28:56.248896982Z","level":"INFO","msg":"stream: closed","id":"4m048f5s"}

wandb/run-20250212_122854-4m048f5s/logs/debug.log

@@ -0,0 +1,26 @@
+2025-02-12 12:28:54,316 INFO    MainThread:224528 [wandb_setup.py:_flush():68] Current SDK version is 0.19.6
+2025-02-12 12:28:54,316 INFO    MainThread:224528 [wandb_setup.py:_flush():68] Configure stats pid to 224528
+2025-02-12 12:28:54,316 INFO    MainThread:224528 [wandb_setup.py:_flush():68] Loading settings from /home/tknika/.config/wandb/settings
+2025-02-12 12:28:54,316 INFO    MainThread:224528 [wandb_setup.py:_flush():68] Loading settings from /home/tknika/xezpeleta/whisper/whisper-small-eu/wandb/settings
+2025-02-12 12:28:54,316 INFO    MainThread:224528 [wandb_setup.py:_flush():68] Loading settings from environment variables
+2025-02-12 12:28:54,316 INFO    MainThread:224528 [wandb_init.py:setup_run_log_directory():637] Logging user logs to /home/tknika/xezpeleta/whisper/whisper-small-eu/wandb/run-20250212_122854-4m048f5s/logs/debug.log
+2025-02-12 12:28:54,316 INFO    MainThread:224528 [wandb_init.py:setup_run_log_directory():638] Logging internal logs to /home/tknika/xezpeleta/whisper/whisper-small-eu/wandb/run-20250212_122854-4m048f5s/logs/debug-internal.log
+2025-02-12 12:28:54,316 INFO    MainThread:224528 [wandb_init.py:init():756] calling init triggers
+2025-02-12 12:28:54,316 INFO    MainThread:224528 [wandb_init.py:init():761] wandb.init called with sweep_config: {}
+config: {'_wandb': {}}
+2025-02-12 12:28:54,316 INFO    MainThread:224528 [wandb_init.py:init():789] starting backend
+2025-02-12 12:28:54,521 INFO    MainThread:224528 [wandb_init.py:init():793] sending inform_init request
+2025-02-12 12:28:54,527 INFO    MainThread:224528 [backend.py:_multiprocessing_setup():97] multiprocessing start_methods=fork,spawn,forkserver, using: spawn
+2025-02-12 12:28:54,528 INFO    MainThread:224528 [wandb_init.py:init():808] backend started and connected
+2025-02-12 12:28:54,530 INFO    MainThread:224528 [wandb_init.py:init():901] updated telemetry
+2025-02-12 12:28:54,537 INFO    MainThread:224528 [wandb_init.py:init():936] communicating run to backend with 90.0 second timeout
+2025-02-12 12:28:54,883 INFO    MainThread:224528 [wandb_init.py:init():994] starting run threads in backend
+2025-02-12 12:28:54,988 INFO    MainThread:224528 [wandb_run.py:_console_start():2385] atexit reg
+2025-02-12 12:28:54,989 INFO    MainThread:224528 [wandb_run.py:_redirect():2235] redirect: wrap_raw
+2025-02-12 12:28:54,989 INFO    MainThread:224528 [wandb_run.py:_redirect():2300] Wrapping output streams.
+2025-02-12 12:28:54,989 INFO    MainThread:224528 [wandb_run.py:_redirect():2325] Redirects installed.
+2025-02-12 12:28:54,990 INFO    MainThread:224528 [wandb_init.py:init():1036] run started, returning control to user process
+2025-02-12 12:28:54,991 INFO    MainThread:224528 [wandb_run.py:_config_callback():1253] config_cb None None {'vocab_size': 51865, 'num_mel_bins': 80, 'd_model': 768, 'encoder_layers': 12, 'encoder_attention_heads': 12, 'decoder_layers': 12, 'decoder_attention_heads': 12, 'decoder_ffn_dim': 3072, 'encoder_ffn_dim': 3072, 'dropout': 0.0, 'attention_dropout': 0.0, 'activation_dropout': 0.0, 'activation_function': 'gelu', 'init_std': 0.02, 'encoder_layerdrop': 0.0, 'decoder_layerdrop': 0.0, 'use_cache': False, 'num_hidden_layers': 12, 'scale_embedding': False, 'max_source_positions': 1500, 'max_target_positions': 448, 'classifier_proj_size': 256, 'use_weighted_layer_sum': False, 'apply_spec_augment': False, 'mask_time_prob': 0.05, 'mask_time_length': 10, 'mask_time_min_masks': 2, 'mask_feature_prob': 0.0, 'mask_feature_length': 10, 'mask_feature_min_masks': 0, 'median_filter_width': 7, 'return_dict': True, 'output_hidden_states': False, 'output_attentions': False, 'torchscript': False, 'torch_dtype': 'float32', 'use_bfloat16': False, 'tf_legacy_loss': False, 'pruned_heads': {}, 'tie_word_embeddings': True, 'chunk_size_feed_forward': 0, 'is_encoder_decoder': True, 'is_decoder': False, 'cross_attention_hidden_size': None, 'add_cross_attention': False, 'tie_encoder_decoder': False, 'max_length': 448, 'min_length': 0, 'do_sample': False, 'early_stopping': False, 'num_beams': 1, 'num_beam_groups': 1, 'diversity_penalty': 0.0, 'temperature': 1.0, 'top_k': 50, 'top_p': 1.0, 'typical_p': 1.0, 'repetition_penalty': 1.0, 'length_penalty': 1.0, 'no_repeat_ngram_size': 0, 'encoder_no_repeat_ngram_size': 0, 'bad_words_ids': None, 'num_return_sequences': 1, 'output_scores': False, 'return_dict_in_generate': False, 'forced_bos_token_id': None, 'forced_eos_token_id': None, 'remove_invalid_values': False, 'exponential_decay_length_penalty': None, 'suppress_tokens': None, 'begin_suppress_tokens': [220, 50257], 'architectures': ['WhisperForConditionalGeneration'], 'finetuning_task': None, 'id2label': {0: 'LABEL_0', 1: 'LABEL_1'}, 'label2id': {'LABEL_0': 0, 'LABEL_1': 1}, 'tokenizer_class': None, 'prefix': None, 'bos_token_id': 50257, 'pad_token_id': 50257, 'eos_token_id': 50257, 'sep_token_id': None, 'decoder_start_token_id': 50258, 'task_specific_params': None, 'problem_type': None, '_name_or_path': 'openai/whisper-small', '_attn_implementation_autoset': True, 'transformers_version': '4.49.0.dev0', 'forced_decoder_ids': None, 'model_type': 'whisper', 'output_dir': './', 'overwrite_output_dir': True, 'do_train': True, 'do_eval': True, 'do_predict': False, 'eval_strategy': 'steps', 'prediction_loss_only': False, 'per_device_train_batch_size': 32, 'per_device_eval_batch_size': 16, 'per_gpu_train_batch_size': None, 'per_gpu_eval_batch_size': None, 'gradient_accumulation_steps': 1, 'eval_accumulation_steps': None, 'eval_delay': 0, 'torch_empty_cache_steps': None, 'learning_rate': 1e-05, 'weight_decay': 0.0, 'adam_beta1': 0.9, 'adam_beta2': 0.999, 'adam_epsilon': 1e-08, 'max_grad_norm': 1.0, 'num_train_epochs': 3.0, 'max_steps': 8000, 'lr_scheduler_type': 'linear', 'lr_scheduler_kwargs': {}, 'warmup_ratio': 0.0, 'warmup_steps': 500, 'log_level': 'passive', 'log_level_replica': 'warning', 'log_on_each_node': True, 'logging_dir': './runs/Feb12_12-28-29_tknika', 'logging_strategy': 'steps', 'logging_first_step': False, 'logging_steps': 25, 'logging_nan_inf_filter': True, 'save_strategy': 'steps', 'save_steps': 1000, 'save_total_limit': None, 'save_safetensors': True, 'save_on_each_node': False, 'save_only_model': False, 'restore_callback_states_from_checkpoint': False, 'no_cuda': False, 'use_cpu': False, 'use_mps_device': False, 'seed': 42, 'data_seed': None, 'jit_mode_eval': False, 'use_ipex': False, 'bf16': False, 'fp16': True, 'fp16_opt_level': 'O1', 'half_precision_backend': 'auto', 'bf16_full_eval': False, 'fp16_full_eval': False, 'tf32': None, 'local_rank': 0, 'ddp_backend': None, 'tpu_num_cores': None, 'tpu_metrics_debug': False, 'debug': [], 'dataloader_drop_last': False, 'eval_steps': 1000, 'dataloader_num_workers': 0, 'dataloader_prefetch_factor': None, 'past_index': -1, 'run_name': 'whisper-small-eu', 'disable_tqdm': False, 'remove_unused_columns': True, 'label_names': None, 'load_best_model_at_end': True, 'metric_for_best_model': 'wer', 'greater_is_better': False, 'ignore_data_skip': False, 'fsdp': [], 'fsdp_min_num_params': 0, 'fsdp_config': {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}, 'fsdp_transformer_layer_cls_to_wrap': None, 'accelerator_config': {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}, 'deepspeed': None, 'label_smoothing_factor': 0.0, 'optim': 'adamw_torch', 'optim_args': None, 'adafactor': False, 'group_by_length': False, 'length_column_name': 'input_length', 'report_to': ['wandb'], 'ddp_find_unused_parameters': None, 'ddp_bucket_cap_mb': None, 'ddp_broadcast_buffers': None, 'dataloader_pin_memory': True, 'dataloader_persistent_workers': False, 'skip_memory_metrics': True, 'use_legacy_prediction_loop': False, 'push_to_hub': True, 'resume_from_checkpoint': None, 'hub_model_id': None, 'hub_strategy': 'every_save', 'hub_token': '<HUB_TOKEN>', 'hub_private_repo': None, 'hub_always_push': False, 'gradient_checkpointing': True, 'gradient_checkpointing_kwargs': None, 'include_inputs_for_metrics': False, 'include_for_metrics': [], 'eval_do_concat_batches': True, 'fp16_backend': 'auto', 'evaluation_strategy': 'steps', 'push_to_hub_model_id': None, 'push_to_hub_organization': None, 'push_to_hub_token': '<PUSH_TO_HUB_TOKEN>', 'mp_parameters': '', 'auto_find_batch_size': False, 'full_determinism': False, 'torchdynamo': None, 'ray_scope': 'last', 'ddp_timeout': 1800, 'torch_compile': False, 'torch_compile_backend': None, 'torch_compile_mode': None, 'dispatch_batches': None, 'split_batches': None, 'include_tokens_per_second': False, 'include_num_input_tokens_seen': False, 'neftune_noise_alpha': None, 'optim_target_modules': None, 'batch_eval_metrics': False, 'eval_on_start': False, 'use_liger_kernel': False, 'eval_use_gather_object': False, 'average_tokens_across_devices': False, 'sortish_sampler': False, 'predict_with_generate': True, 'generation_max_length': 225, 'generation_num_beams': None, 'generation_config': None}
+2025-02-12 12:28:54,995 INFO    MainThread:224528 [wandb_config.py:__setitem__():154] config set model/num_parameters = 241734912 - <bound method Run._config_callback of <wandb.sdk.wandb_run.Run object at 0x71c5f6c57cb0>>
+2025-02-12 12:28:54,995 INFO    MainThread:224528 [wandb_run.py:_config_callback():1253] config_cb model/num_parameters 241734912 None
+2025-02-12 12:28:55,029 WARNING MsgRouterThr:224528 [router.py:message_loop():75] message_loop has been closed

wandb/run-20250212_125202-c6xjc1gs/files/config.yaml

@@ -0,0 +1,512 @@
+_attn_implementation_autoset:
+    value: true
+_name_or_path:
+    value: openai/whisper-small
+_wandb:
+    value:
+        cli_version: 0.19.6
+        m:
+            - "1": train/global_step
+              "6":
+                - 3
+              "7": []
+        python_version: 3.12.3
+        t:
+            "1":
+                - 1
+                - 5
+                - 11
+                - 49
+                - 51
+                - 53
+                - 55
+                - 71
+                - 100
+            "2":
+                - 1
+                - 5
+                - 11
+                - 49
+                - 51
+                - 53
+                - 55
+                - 71
+                - 100
+            "3":
+                - 7
+                - 13
+                - 19
+                - 23
+                - 55
+                - 66
+            "4": 3.12.3
+            "5": 0.19.6
+            "6": 4.49.0.dev0
+            "8":
+                - 5
+            "9":
+                "1": transformers_trainer
+            "12": 0.19.6
+            "13": linux-x86_64
+accelerator_config:
+    value:
+        dispatch_batches: null
+        even_batches: true
+        gradient_accumulation_kwargs: null
+        non_blocking: false
+        split_batches: false
+        use_seedable_sampler: true
+activation_dropout:
+    value: 0
+activation_function:
+    value: gelu
+adafactor:
+    value: false
+adam_beta1:
+    value: 0.9
+adam_beta2:
+    value: 0.999
+adam_epsilon:
+    value: 1e-08
+add_cross_attention:
+    value: false
+apply_spec_augment:
+    value: false
+architectures:
+    value:
+        - WhisperForConditionalGeneration
+attention_dropout:
+    value: 0
+auto_find_batch_size:
+    value: false
+average_tokens_across_devices:
+    value: false
+bad_words_ids:
+    value: null
+batch_eval_metrics:
+    value: false
+begin_suppress_tokens:
+    value:
+        - 220
+        - 50257
+bf16:
+    value: false
+bf16_full_eval:
+    value: false
+bos_token_id:
+    value: 50257
+chunk_size_feed_forward:
+    value: 0
+classifier_proj_size:
+    value: 256
+cross_attention_hidden_size:
+    value: null
+d_model:
+    value: 768
+data_seed:
+    value: null
+dataloader_drop_last:
+    value: false
+dataloader_num_workers:
+    value: 0
+dataloader_persistent_workers:
+    value: false
+dataloader_pin_memory:
+    value: true
+dataloader_prefetch_factor:
+    value: null
+ddp_backend:
+    value: null
+ddp_broadcast_buffers:
+    value: null
+ddp_bucket_cap_mb:
+    value: null
+ddp_find_unused_parameters:
+    value: null
+ddp_timeout:
+    value: 1800
+debug:
+    value: []
+decoder_attention_heads:
+    value: 12
+decoder_ffn_dim:
+    value: 3072
+decoder_layerdrop:
+    value: 0
+decoder_layers:
+    value: 12
+decoder_start_token_id:
+    value: 50258
+deepspeed:
+    value: null
+disable_tqdm:
+    value: false
+dispatch_batches:
+    value: null
+diversity_penalty:
+    value: 0
+do_eval:
+    value: true
+do_predict:
+    value: false
+do_sample:
+    value: false
+do_train:
+    value: true
+dropout:
+    value: 0
+early_stopping:
+    value: false
+encoder_attention_heads:
+    value: 12
+encoder_ffn_dim:
+    value: 3072
+encoder_layerdrop:
+    value: 0
+encoder_layers:
+    value: 12
+encoder_no_repeat_ngram_size:
+    value: 0
+eos_token_id:
+    value: 50257
+eval_accumulation_steps:
+    value: null
+eval_delay:
+    value: 0
+eval_do_concat_batches:
+    value: true
+eval_on_start:
+    value: false
+eval_steps:
+    value: 1000
+eval_strategy:
+    value: steps
+eval_use_gather_object:
+    value: false
+evaluation_strategy:
+    value: steps
+exponential_decay_length_penalty:
+    value: null
+finetuning_task:
+    value: null
+forced_bos_token_id:
+    value: null
+forced_decoder_ids:
+    value: null
+forced_eos_token_id:
+    value: null
+fp16:
+    value: true
+fp16_backend:
+    value: auto
+fp16_full_eval:
+    value: false
+fp16_opt_level:
+    value: O1
+fsdp:
+    value: []
+fsdp_config:
+    value:
+        min_num_params: 0
+        xla: false
+        xla_fsdp_grad_ckpt: false
+        xla_fsdp_v2: false
+fsdp_min_num_params:
+    value: 0
+fsdp_transformer_layer_cls_to_wrap:
+    value: null
+full_determinism:
+    value: false
+generation_config:
+    value: null
+generation_max_length:
+    value: 225
+generation_num_beams:
+    value: null
+gradient_accumulation_steps:
+    value: 1
+gradient_checkpointing:
+    value: true
+gradient_checkpointing_kwargs:
+    value: null
+greater_is_better:
+    value: false
+group_by_length:
+    value: false
+half_precision_backend:
+    value: auto
+hub_always_push:
+    value: false
+hub_model_id:
+    value: null
+hub_private_repo:
+    value: null
+hub_strategy:
+    value: every_save
+hub_token:
+    value: <HUB_TOKEN>
+id2label:
+    value:
+        "0": LABEL_0
+        "1": LABEL_1
+ignore_data_skip:
+    value: false
+include_for_metrics:
+    value: []
+include_inputs_for_metrics:
+    value: false
+include_num_input_tokens_seen:
+    value: false
+include_tokens_per_second:
+    value: false
+init_std:
+    value: 0.02
+is_decoder:
+    value: false
+is_encoder_decoder:
+    value: true
+jit_mode_eval:
+    value: false
+label_names:
+    value: null
+label_smoothing_factor:
+    value: 0
+label2id:
+    value:
+        LABEL_0: 0
+        LABEL_1: 1
+learning_rate:
+    value: 1e-05
+length_column_name:
+    value: input_length
+length_penalty:
+    value: 1
+load_best_model_at_end:
+    value: true
+local_rank:
+    value: 0
+log_level:
+    value: passive
+log_level_replica:
+    value: warning
+log_on_each_node:
+    value: true
+logging_dir:
+    value: ./runs/Feb12_12-51-48_tknika
+logging_first_step:
+    value: false
+logging_nan_inf_filter:
+    value: true
+logging_steps:
+    value: 25
+logging_strategy:
+    value: steps
+lr_scheduler_type:
+    value: linear
+mask_feature_length:
+    value: 10
+mask_feature_min_masks:
+    value: 0
+mask_feature_prob:
+    value: 0
+mask_time_length:
+    value: 10
+mask_time_min_masks:
+    value: 2
+mask_time_prob:
+    value: 0.05
+max_grad_norm:
+    value: 1
+max_length:
+    value: 448
+max_source_positions:
+    value: 1500
+max_steps:
+    value: 8000
+max_target_positions:
+    value: 448
+median_filter_width:
+    value: 7
+metric_for_best_model:
+    value: wer
+min_length:
+    value: 0
+model/num_parameters:
+    value: 241734912
+model_type:
+    value: whisper
+mp_parameters:
+    value: ""
+neftune_noise_alpha:
+    value: null
+no_cuda:
+    value: false
+no_repeat_ngram_size:
+    value: 0
+num_beam_groups:
+    value: 1
+num_beams:
+    value: 1
+num_hidden_layers:
+    value: 12
+num_mel_bins:
+    value: 80
+num_return_sequences:
+    value: 1
+num_train_epochs:
+    value: 3
+optim:
+    value: adamw_torch
+optim_args:
+    value: null
+optim_target_modules:
+    value: null
+output_attentions:
+    value: false
+output_dir:
+    value: ./
+output_hidden_states:
+    value: false
+output_scores:
+    value: false
+overwrite_output_dir:
+    value: true
+pad_token_id:
+    value: 50257
+past_index:
+    value: -1
+per_device_eval_batch_size:
+    value: 16
+per_device_train_batch_size:
+    value: 32
+per_gpu_eval_batch_size:
+    value: null
+per_gpu_train_batch_size:
+    value: null
+predict_with_generate:
+    value: true
+prediction_loss_only:
+    value: false
+prefix:
+    value: null
+problem_type:
+    value: null
+push_to_hub:
+    value: true
+push_to_hub_model_id:
+    value: null
+push_to_hub_organization:
+    value: null
+push_to_hub_token:
+    value: <PUSH_TO_HUB_TOKEN>
+ray_scope:
+    value: last
+remove_invalid_values:
+    value: false
+remove_unused_columns:
+    value: true
+repetition_penalty:
+    value: 1
+report_to:
+    value:
+        - wandb
+restore_callback_states_from_checkpoint:
+    value: false
+resume_from_checkpoint:
+    value: null
+return_dict:
+    value: true
+return_dict_in_generate:
+    value: false
+run_name:
+    value: whisper-small-eu
+save_on_each_node:
+    value: false
+save_only_model:
+    value: false
+save_safetensors:
+    value: true
+save_steps:
+    value: 1000
+save_strategy:
+    value: steps
+save_total_limit:
+    value: null
+scale_embedding:
+    value: false
+seed:
+    value: 42
+sep_token_id:
+    value: null
+skip_memory_metrics:
+    value: true
+sortish_sampler:
+    value: false
+split_batches:
+    value: null
+suppress_tokens:
+    value: null
+task_specific_params:
+    value: null
+temperature:
+    value: 1
+tf_legacy_loss:
+    value: false
+tf32:
+    value: null
+tie_encoder_decoder:
+    value: false
+tie_word_embeddings:
+    value: true
+tokenizer_class:
+    value: null
+top_k:
+    value: 50
+top_p:
+    value: 1
+torch_compile:
+    value: false
+torch_compile_backend:
+    value: null
+torch_compile_mode:
+    value: null
+torch_dtype:
+    value: float32
+torch_empty_cache_steps:
+    value: null
+torchdynamo:
+    value: null
+torchscript:
+    value: false
+tpu_metrics_debug:
+    value: false
+tpu_num_cores:
+    value: null
+transformers_version:
+    value: 4.49.0.dev0
+typical_p:
+    value: 1
+use_bfloat16:
+    value: false
+use_cache:
+    value: false
+use_cpu:
+    value: false
+use_ipex:
+    value: false
+use_legacy_prediction_loop:
+    value: false
+use_liger_kernel:
+    value: false
+use_mps_device:
+    value: false
+use_weighted_layer_sum:
+    value: false
+vocab_size:
+    value: 51865
+warmup_ratio:
+    value: 0
+warmup_steps:
+    value: 500
+weight_decay:
+    value: 0

wandb/run-20250212_125202-c6xjc1gs/files/output.log

@@ -0,0 +1,22 @@
+  0%|                                                                                                                                               | 0/8000 [00:00<?, ?it/s]Traceback (most recent call last):
+  File "/home/tknika/xezpeleta/whisper/whisper-small-eu/run_speech_recognition_seq2seq_streaming.py", line 630, in <module>
+    main()
+  File "/home/tknika/xezpeleta/whisper/whisper-small-eu/run_speech_recognition_seq2seq_streaming.py", line 579, in main
+    train_result = trainer.train(resume_from_checkpoint=checkpoint)
+                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/tknika/xezpeleta/whisper/whisper-small-eu/.venv/lib/python3.12/site-packages/transformers/trainer.py", line 2197, in train
+    return inner_training_loop(
+           ^^^^^^^^^^^^^^^^^^^^
+  File "/home/tknika/xezpeleta/whisper/whisper-small-eu/.venv/lib/python3.12/site-packages/transformers/trainer.py", line 2438, in _inner_training_loop
+    self.control = self.callback_handler.on_epoch_begin(args, self.state, self.control)
+                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/tknika/xezpeleta/whisper/whisper-small-eu/.venv/lib/python3.12/site-packages/transformers/trainer_callback.py", line 514, in on_epoch_begin
+    return self.call_event("on_epoch_begin", args, state, control)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/tknika/xezpeleta/whisper/whisper-small-eu/.venv/lib/python3.12/site-packages/transformers/trainer_callback.py", line 557, in call_event
+    result = getattr(callback, event)(
+             ^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/tknika/xezpeleta/whisper/whisper-small-eu/run_speech_recognition_seq2seq_streaming.py", line 555, in on_epoch_begin
+    if isinstance(train_dataloader.dataset, IterableDatasetShard):
+                  ^^^^^^^^^^^^^^^^^^^^^^^^
+AttributeError: 'NoneType' object has no attribute 'dataset'

wandb/run-20250212_125202-c6xjc1gs/files/requirements.txt

@@ -0,0 +1,115 @@
+aiosignal==1.3.2
+Markdown==3.7
+more-itertools==10.6.0
+requests==2.32.3
+sentry-sdk==2.21.0
+torchaudio==2.6.0
+charset-normalizer==3.4.1
+docker-pycreds==0.4.0
+nvidia-cusolver-cu12==11.6.1.9
+PyYAML==6.0.2
+librosa==0.10.2.post1
+soxr==0.5.0.post1
+multiprocess==0.70.16
+setuptools==75.8.0
+nvidia-cufft-cu12==11.2.1.3
+joblib==1.4.2
+pytz==2025.1
+pip==24.0
+scikit-learn==1.6.1
+certifi==2025.1.31
+jiwer==3.1.0
+regex==2024.11.6
+annotated-types==0.7.0
+grpcio==1.70.0
+msgpack==1.1.0
+mpmath==1.3.0
+nvidia-cudnn-cu12==9.1.0.70
+soundfile==0.13.1
+dill==0.3.8
+nvidia-nvtx-cu12==12.4.127
+six==1.17.0
+nvidia-cuda-cupti-cu12==12.4.127
+pyarrow==19.0.0
+nvidia-nccl-cu12==2.21.5
+psutil==6.1.1
+decorator==5.1.1
+llvmlite==0.44.0
+frozenlist==1.5.0
+pydantic==2.10.6
+networkx==3.4.2
+idna==3.10
+wandb==0.19.6
+aiohttp==3.11.12
+RapidFuzz==3.12.1
+pandas==2.2.3
+python-dateutil==2.9.0.post0
+numpy==2.1.3
+tokenizers==0.21.0
+nvidia-cusparselt-cu12==0.6.2
+typing_extensions==4.12.2
+urllib3==2.3.0
+setproctitle==1.3.4
+tzdata==2025.1
+sympy==1.13.1
+pooch==1.8.2
+click==8.1.8
+pydantic_core==2.27.2
+MarkupSafe==3.0.2
+scipy==1.15.1
+accelerate==1.3.0
+tensorboard==2.19.0
+protobuf==5.29.3
+gitdb==4.0.12
+smmap==5.0.2
+absl-py==2.1.0
+tqdm==4.67.1
+yarl==1.18.3
+pycparser==2.22
+nvidia-cusparse-cu12==12.3.1.170
+attrs==25.1.0
+lazy_loader==0.4
+tensorboard-data-server==0.7.2
+threadpoolctl==3.5.0
+GitPython==3.1.44
+safetensors==0.5.2
+fsspec==2024.12.0
+nvidia-cuda-nvrtc-cu12==12.4.127
+filelock==3.17.0
+aiohappyeyeballs==2.4.6
+packaging==24.2
+datasets==3.2.1.dev0
+audioread==3.0.1
+propcache==0.2.1
+transformers==4.49.0.dev0
+nvidia-cuda-runtime-cu12==12.4.127
+cffi==1.17.1
+evaluate==0.4.3
+Werkzeug==3.1.3
+huggingface-hub==0.28.1
+Jinja2==3.1.5
+torch==2.6.0
+nvidia-curand-cu12==10.3.5.147
+xxhash==3.5.0
+platformdirs==4.3.6
+multidict==6.1.0
+nvidia-cublas-cu12==12.4.5.8
+nvidia-nvjitlink-cu12==12.4.127
+triton==3.2.0
+numba==0.61.0
+importlib_metadata==8.0.0
+platformdirs==4.2.2
+typeguard==4.3.0
+more-itertools==10.3.0
+tomli==2.0.1
+autocommand==2.2.2
+zipp==3.19.2
+typing_extensions==4.12.2
+backports.tarfile==1.2.0
+inflect==7.3.1
+jaraco.text==3.12.1
+wheel==0.43.0
+packaging==24.2
+jaraco.collections==5.1.0
+jaraco.functools==4.0.1
+jaraco.context==5.3.0

wandb/run-20250212_125202-c6xjc1gs/files/wandb-metadata.json

@@ -0,0 +1,85 @@
+{
+  "os":  "Linux-6.8.0-48-generic-x86_64-with-glibc2.39",
+  "python":  "CPython 3.12.3",
+  "startedAt":  "2025-02-12T12:52:03.105234Z",
+  "args":  [
+    "--model_name_or_path=openai/whisper-small",
+    "--dataset_name=asierhv/composite_corpus_eu_v2.1",
+    "--language=basque",
+    "--train_split_name=train",
+    "--eval_split_name=test_parl",
+    "--model_index_name=Whisper Small Basque",
+    "--max_steps=8000",
+    "--output_dir=./",
+    "--per_device_train_batch_size=32",
+    "--per_device_eval_batch_size=16",
+    "--gradient_accumulation_steps=1",
+    "--logging_steps=25",
+    "--learning_rate=1e-5",
+    "--warmup_steps=500",
+    "--evaluation_strategy=steps",
+    "--eval_steps=1000",
+    "--save_strategy=steps",
+    "--save_steps=1000",
+    "--generation_max_length=225",
+    "--length_column_name=input_length",
+    "--max_duration_in_seconds=30",
+    "--text_column_name=sentence",
+    "--freeze_feature_encoder=False",
+    "--report_to=tensorboard",
+    "--metric_for_best_model=wer",
+    "--greater_is_better=False",
+    "--load_best_model_at_end",
+    "--gradient_checkpointing",
+    "--fp16",
+    "--overwrite_output_dir",
+    "--do_train",
+    "--do_eval",
+    "--predict_with_generate",
+    "--do_normalize_eval",
+    "--streaming",
+    "--use_auth_token",
+    "--push_to_hub",
+    "--report_to",
+    "wandb",
+    "--run_name",
+    "whisper-small-eu"
+  ],
+  "program":  "/home/tknika/xezpeleta/whisper/whisper-small-eu/run_speech_recognition_seq2seq_streaming.py",
+  "codePath":  "run_speech_recognition_seq2seq_streaming.py",
+  "git":  {
+    "remote":  "https://huggingface.co/xezpeleta/whisper-small-eu",
+    "commit":  "9c975864b20b4df94398a870e97cad2934253ec3"
+  },
+  "email":  "xezpeleta@gmail.com",
+  "root":  "/home/tknika/xezpeleta/whisper/whisper-small-eu",
+  "host":  "tknika",
+  "executable":  "/home/tknika/xezpeleta/whisper/whisper-small-eu/.venv/bin/python",
+  "codePathLocal":  "run_speech_recognition_seq2seq_streaming.py",
+  "cpu_count":  8,
+  "cpu_count_logical":  8,
+  "gpu":  "NVIDIA L40-48Q",
+  "gpu_count":  1,
+  "disk":  {
+    "/":  {
+      "total":  "525987168256",
+      "used":  "313777016832"
+    }
+  },
+  "memory":  {
+    "total":  "33654022144"
+  },
+  "cpu":  {
+    "count":  8,
+    "countLogical":  8
+  },
+  "gpu_nvidia":  [
+    {
+      "name":  "NVIDIA L40-48Q",
+      "memoryTotal":  "51539607552",
+      "cudaCores":  18176,
+      "architecture":  "Ada"
+    }
+  ],
+  "cudaVersion":  "12.4"
+}

wandb/run-20250212_125202-c6xjc1gs/files/wandb-summary.json

@@ -0,0 +1 @@
+{"_wandb":{"runtime":0}}

wandb/run-20250212_125202-c6xjc1gs/logs/debug-core.log

@@ -0,0 +1,14 @@
+{"time":"2025-02-12T12:52:02.919881508Z","level":"INFO","msg":"main: starting server","port-filename":"/tmp/tmpeae6bnaj/port-226112.txt","pid":226112,"log-level":0,"disable-analytics":false,"shutdown-on-parent-exit":false}
+{"time":"2025-02-12T12:52:02.924775623Z","level":"INFO","msg":"Will exit if parent process dies.","ppid":226112}
+{"time":"2025-02-12T12:52:02.924741833Z","level":"INFO","msg":"server is running","addr":{"IP":"127.0.0.1","Port":37305,"Zone":""}}
+{"time":"2025-02-12T12:52:03.098177175Z","level":"INFO","msg":"connection: ManageConnectionData: new connection created","id":"127.0.0.1:34596"}
+{"time":"2025-02-12T12:52:03.107916075Z","level":"INFO","msg":"handleInformInit: received","streamId":"c6xjc1gs","id":"127.0.0.1:34596"}
+{"time":"2025-02-12T12:52:03.213738528Z","level":"INFO","msg":"handleInformInit: stream started","streamId":"c6xjc1gs","id":"127.0.0.1:34596"}
+{"time":"2025-02-12T12:52:03.606976673Z","level":"INFO","msg":"handleInformTeardown: server teardown initiated","id":"127.0.0.1:34596"}
+{"time":"2025-02-12T12:52:03.607096473Z","level":"INFO","msg":"connection: closing","id":"127.0.0.1:34596"}
+{"time":"2025-02-12T12:52:03.607114372Z","level":"INFO","msg":"server is shutting down"}
+{"time":"2025-02-12T12:52:03.607218922Z","level":"INFO","msg":"connection: closed successfully","id":"127.0.0.1:34596"}
+{"time":"2025-02-12T12:52:03.804235797Z","level":"ERROR","msg":"processOutgoingData: flush error","error":"write tcp 127.0.0.1:37305->127.0.0.1:34596: use of closed network connection","id":"127.0.0.1:34596"}
+{"time":"2025-02-12T12:52:05.13436235Z","level":"INFO","msg":"handleInformTeardown: server shutdown complete","id":"127.0.0.1:34596"}
+{"time":"2025-02-12T12:52:05.13438775Z","level":"INFO","msg":"connection: ManageConnectionData: connection closed","id":"127.0.0.1:34596"}
+{"time":"2025-02-12T12:52:05.13441372Z","level":"INFO","msg":"server is closed"}

wandb/run-20250212_125202-c6xjc1gs/logs/debug-internal.log

@@ -0,0 +1,15 @@
+{"time":"2025-02-12T12:52:03.108316863Z","level":"INFO","msg":"stream: starting","core version":"0.19.6","symlink path":"/home/tknika/xezpeleta/whisper/whisper-small-eu/wandb/run-20250212_125202-c6xjc1gs/logs/debug-core.log"}
+{"time":"2025-02-12T12:52:03.213666458Z","level":"INFO","msg":"created new stream","id":"c6xjc1gs"}
+{"time":"2025-02-12T12:52:03.213728098Z","level":"INFO","msg":"stream: started","id":"c6xjc1gs"}
+{"time":"2025-02-12T12:52:03.213779117Z","level":"INFO","msg":"writer: Do: started","stream_id":"c6xjc1gs"}
+{"time":"2025-02-12T12:52:03.213809587Z","level":"INFO","msg":"handler: started","stream_id":"c6xjc1gs"}
+{"time":"2025-02-12T12:52:03.214018716Z","level":"INFO","msg":"sender: started","stream_id":"c6xjc1gs"}
+{"time":"2025-02-12T12:52:03.484749537Z","level":"INFO","msg":"Starting system monitor"}
+{"time":"2025-02-12T12:52:03.607062513Z","level":"INFO","msg":"stream: closing","id":"c6xjc1gs"}
+{"time":"2025-02-12T12:52:03.607125442Z","level":"INFO","msg":"Stopping system monitor"}
+{"time":"2025-02-12T12:52:03.607814399Z","level":"INFO","msg":"Stopped system monitor"}
+{"time":"2025-02-12T12:52:04.912814278Z","level":"INFO","msg":"fileTransfer: Close: file transfer manager closed"}
+{"time":"2025-02-12T12:52:05.133965652Z","level":"INFO","msg":"handler: closed","stream_id":"c6xjc1gs"}
+{"time":"2025-02-12T12:52:05.134024822Z","level":"INFO","msg":"sender: closed","stream_id":"c6xjc1gs"}
+{"time":"2025-02-12T12:52:05.134018042Z","level":"INFO","msg":"writer: Close: closed","stream_id":"c6xjc1gs"}
+{"time":"2025-02-12T12:52:05.134218211Z","level":"INFO","msg":"stream: closed","id":"c6xjc1gs"}

wandb/run-20250212_125202-c6xjc1gs/logs/debug.log

@@ -0,0 +1,26 @@
+2025-02-12 12:52:02,886 INFO    MainThread:226112 [wandb_setup.py:_flush():68] Current SDK version is 0.19.6
+2025-02-12 12:52:02,887 INFO    MainThread:226112 [wandb_setup.py:_flush():68] Configure stats pid to 226112
+2025-02-12 12:52:02,887 INFO    MainThread:226112 [wandb_setup.py:_flush():68] Loading settings from /home/tknika/.config/wandb/settings
+2025-02-12 12:52:02,887 INFO    MainThread:226112 [wandb_setup.py:_flush():68] Loading settings from /home/tknika/xezpeleta/whisper/whisper-small-eu/wandb/settings
+2025-02-12 12:52:02,887 INFO    MainThread:226112 [wandb_setup.py:_flush():68] Loading settings from environment variables
+2025-02-12 12:52:02,887 INFO    MainThread:226112 [wandb_init.py:setup_run_log_directory():637] Logging user logs to /home/tknika/xezpeleta/whisper/whisper-small-eu/wandb/run-20250212_125202-c6xjc1gs/logs/debug.log
+2025-02-12 12:52:02,887 INFO    MainThread:226112 [wandb_init.py:setup_run_log_directory():638] Logging internal logs to /home/tknika/xezpeleta/whisper/whisper-small-eu/wandb/run-20250212_125202-c6xjc1gs/logs/debug-internal.log
+2025-02-12 12:52:02,887 INFO    MainThread:226112 [wandb_init.py:init():756] calling init triggers
+2025-02-12 12:52:02,887 INFO    MainThread:226112 [wandb_init.py:init():761] wandb.init called with sweep_config: {}
+config: {'_wandb': {}}
+2025-02-12 12:52:02,887 INFO    MainThread:226112 [wandb_init.py:init():789] starting backend
+2025-02-12 12:52:03,097 INFO    MainThread:226112 [wandb_init.py:init():793] sending inform_init request
+2025-02-12 12:52:03,104 INFO    MainThread:226112 [backend.py:_multiprocessing_setup():97] multiprocessing start_methods=fork,spawn,forkserver, using: spawn
+2025-02-12 12:52:03,104 INFO    MainThread:226112 [wandb_init.py:init():808] backend started and connected
+2025-02-12 12:52:03,107 INFO    MainThread:226112 [wandb_init.py:init():901] updated telemetry
+2025-02-12 12:52:03,114 INFO    MainThread:226112 [wandb_init.py:init():936] communicating run to backend with 90.0 second timeout
+2025-02-12 12:52:03,483 INFO    MainThread:226112 [wandb_init.py:init():994] starting run threads in backend
+2025-02-12 12:52:03,566 INFO    MainThread:226112 [wandb_run.py:_console_start():2385] atexit reg
+2025-02-12 12:52:03,566 INFO    MainThread:226112 [wandb_run.py:_redirect():2235] redirect: wrap_raw
+2025-02-12 12:52:03,566 INFO    MainThread:226112 [wandb_run.py:_redirect():2300] Wrapping output streams.
+2025-02-12 12:52:03,566 INFO    MainThread:226112 [wandb_run.py:_redirect():2325] Redirects installed.
+2025-02-12 12:52:03,568 INFO    MainThread:226112 [wandb_init.py:init():1036] run started, returning control to user process
+2025-02-12 12:52:03,569 INFO    MainThread:226112 [wandb_run.py:_config_callback():1253] config_cb None None {'vocab_size': 51865, 'num_mel_bins': 80, 'd_model': 768, 'encoder_layers': 12, 'encoder_attention_heads': 12, 'decoder_layers': 12, 'decoder_attention_heads': 12, 'decoder_ffn_dim': 3072, 'encoder_ffn_dim': 3072, 'dropout': 0.0, 'attention_dropout': 0.0, 'activation_dropout': 0.0, 'activation_function': 'gelu', 'init_std': 0.02, 'encoder_layerdrop': 0.0, 'decoder_layerdrop': 0.0, 'use_cache': False, 'num_hidden_layers': 12, 'scale_embedding': False, 'max_source_positions': 1500, 'max_target_positions': 448, 'classifier_proj_size': 256, 'use_weighted_layer_sum': False, 'apply_spec_augment': False, 'mask_time_prob': 0.05, 'mask_time_length': 10, 'mask_time_min_masks': 2, 'mask_feature_prob': 0.0, 'mask_feature_length': 10, 'mask_feature_min_masks': 0, 'median_filter_width': 7, 'return_dict': True, 'output_hidden_states': False, 'output_attentions': False, 'torchscript': False, 'torch_dtype': 'float32', 'use_bfloat16': False, 'tf_legacy_loss': False, 'pruned_heads': {}, 'tie_word_embeddings': True, 'chunk_size_feed_forward': 0, 'is_encoder_decoder': True, 'is_decoder': False, 'cross_attention_hidden_size': None, 'add_cross_attention': False, 'tie_encoder_decoder': False, 'max_length': 448, 'min_length': 0, 'do_sample': False, 'early_stopping': False, 'num_beams': 1, 'num_beam_groups': 1, 'diversity_penalty': 0.0, 'temperature': 1.0, 'top_k': 50, 'top_p': 1.0, 'typical_p': 1.0, 'repetition_penalty': 1.0, 'length_penalty': 1.0, 'no_repeat_ngram_size': 0, 'encoder_no_repeat_ngram_size': 0, 'bad_words_ids': None, 'num_return_sequences': 1, 'output_scores': False, 'return_dict_in_generate': False, 'forced_bos_token_id': None, 'forced_eos_token_id': None, 'remove_invalid_values': False, 'exponential_decay_length_penalty': None, 'suppress_tokens': None, 'begin_suppress_tokens': [220, 50257], 'architectures': ['WhisperForConditionalGeneration'], 'finetuning_task': None, 'id2label': {0: 'LABEL_0', 1: 'LABEL_1'}, 'label2id': {'LABEL_0': 0, 'LABEL_1': 1}, 'tokenizer_class': None, 'prefix': None, 'bos_token_id': 50257, 'pad_token_id': 50257, 'eos_token_id': 50257, 'sep_token_id': None, 'decoder_start_token_id': 50258, 'task_specific_params': None, 'problem_type': None, '_name_or_path': 'openai/whisper-small', '_attn_implementation_autoset': True, 'transformers_version': '4.49.0.dev0', 'forced_decoder_ids': None, 'model_type': 'whisper', 'output_dir': './', 'overwrite_output_dir': True, 'do_train': True, 'do_eval': True, 'do_predict': False, 'eval_strategy': 'steps', 'prediction_loss_only': False, 'per_device_train_batch_size': 32, 'per_device_eval_batch_size': 16, 'per_gpu_train_batch_size': None, 'per_gpu_eval_batch_size': None, 'gradient_accumulation_steps': 1, 'eval_accumulation_steps': None, 'eval_delay': 0, 'torch_empty_cache_steps': None, 'learning_rate': 1e-05, 'weight_decay': 0.0, 'adam_beta1': 0.9, 'adam_beta2': 0.999, 'adam_epsilon': 1e-08, 'max_grad_norm': 1.0, 'num_train_epochs': 3.0, 'max_steps': 8000, 'lr_scheduler_type': 'linear', 'lr_scheduler_kwargs': {}, 'warmup_ratio': 0.0, 'warmup_steps': 500, 'log_level': 'passive', 'log_level_replica': 'warning', 'log_on_each_node': True, 'logging_dir': './runs/Feb12_12-51-48_tknika', 'logging_strategy': 'steps', 'logging_first_step': False, 'logging_steps': 25, 'logging_nan_inf_filter': True, 'save_strategy': 'steps', 'save_steps': 1000, 'save_total_limit': None, 'save_safetensors': True, 'save_on_each_node': False, 'save_only_model': False, 'restore_callback_states_from_checkpoint': False, 'no_cuda': False, 'use_cpu': False, 'use_mps_device': False, 'seed': 42, 'data_seed': None, 'jit_mode_eval': False, 'use_ipex': False, 'bf16': False, 'fp16': True, 'fp16_opt_level': 'O1', 'half_precision_backend': 'auto', 'bf16_full_eval': False, 'fp16_full_eval': False, 'tf32': None, 'local_rank': 0, 'ddp_backend': None, 'tpu_num_cores': None, 'tpu_metrics_debug': False, 'debug': [], 'dataloader_drop_last': False, 'eval_steps': 1000, 'dataloader_num_workers': 0, 'dataloader_prefetch_factor': None, 'past_index': -1, 'run_name': 'whisper-small-eu', 'disable_tqdm': False, 'remove_unused_columns': True, 'label_names': None, 'load_best_model_at_end': True, 'metric_for_best_model': 'wer', 'greater_is_better': False, 'ignore_data_skip': False, 'fsdp': [], 'fsdp_min_num_params': 0, 'fsdp_config': {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}, 'fsdp_transformer_layer_cls_to_wrap': None, 'accelerator_config': {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}, 'deepspeed': None, 'label_smoothing_factor': 0.0, 'optim': 'adamw_torch', 'optim_args': None, 'adafactor': False, 'group_by_length': False, 'length_column_name': 'input_length', 'report_to': ['wandb'], 'ddp_find_unused_parameters': None, 'ddp_bucket_cap_mb': None, 'ddp_broadcast_buffers': None, 'dataloader_pin_memory': True, 'dataloader_persistent_workers': False, 'skip_memory_metrics': True, 'use_legacy_prediction_loop': False, 'push_to_hub': True, 'resume_from_checkpoint': None, 'hub_model_id': None, 'hub_strategy': 'every_save', 'hub_token': '<HUB_TOKEN>', 'hub_private_repo': None, 'hub_always_push': False, 'gradient_checkpointing': True, 'gradient_checkpointing_kwargs': None, 'include_inputs_for_metrics': False, 'include_for_metrics': [], 'eval_do_concat_batches': True, 'fp16_backend': 'auto', 'evaluation_strategy': 'steps', 'push_to_hub_model_id': None, 'push_to_hub_organization': None, 'push_to_hub_token': '<PUSH_TO_HUB_TOKEN>', 'mp_parameters': '', 'auto_find_batch_size': False, 'full_determinism': False, 'torchdynamo': None, 'ray_scope': 'last', 'ddp_timeout': 1800, 'torch_compile': False, 'torch_compile_backend': None, 'torch_compile_mode': None, 'dispatch_batches': None, 'split_batches': None, 'include_tokens_per_second': False, 'include_num_input_tokens_seen': False, 'neftune_noise_alpha': None, 'optim_target_modules': None, 'batch_eval_metrics': False, 'eval_on_start': False, 'use_liger_kernel': False, 'eval_use_gather_object': False, 'average_tokens_across_devices': False, 'sortish_sampler': False, 'predict_with_generate': True, 'generation_max_length': 225, 'generation_num_beams': None, 'generation_config': None}
+2025-02-12 12:52:03,571 INFO    MainThread:226112 [wandb_config.py:__setitem__():154] config set model/num_parameters = 241734912 - <bound method Run._config_callback of <wandb.sdk.wandb_run.Run object at 0x7d4830f2ddf0>>
+2025-02-12 12:52:03,571 INFO    MainThread:226112 [wandb_run.py:_config_callback():1253] config_cb model/num_parameters 241734912 None
+2025-02-12 12:52:03,607 WARNING MsgRouterThr:226112 [router.py:message_loop():75] message_loop has been closed

wandb/run-20250212_125924-xhsgsxqq/files/config.yaml

@@ -0,0 +1,512 @@
+_attn_implementation_autoset:
+    value: true
+_name_or_path:
+    value: openai/whisper-small
+_wandb:
+    value:
+        cli_version: 0.19.6
+        m:
+            - "1": train/global_step
+              "6":
+                - 3
+              "7": []
+        python_version: 3.12.3
+        t:
+            "1":
+                - 1
+                - 5
+                - 11
+                - 49
+                - 51
+                - 53
+                - 55
+                - 71
+                - 100
+            "2":
+                - 1
+                - 5
+                - 11
+                - 49
+                - 51
+                - 53
+                - 55
+                - 71
+                - 100
+            "3":
+                - 7
+                - 13
+                - 19
+                - 23
+                - 55
+                - 66
+            "4": 3.12.3
+            "5": 0.19.6
+            "6": 4.49.0.dev0
+            "8":
+                - 5
+            "9":
+                "1": transformers_trainer
+            "12": 0.19.6
+            "13": linux-x86_64
+accelerator_config:
+    value:
+        dispatch_batches: null
+        even_batches: true
+        gradient_accumulation_kwargs: null
+        non_blocking: false
+        split_batches: false
+        use_seedable_sampler: true
+activation_dropout:
+    value: 0
+activation_function:
+    value: gelu
+adafactor:
+    value: false
+adam_beta1:
+    value: 0.9
+adam_beta2:
+    value: 0.999
+adam_epsilon:
+    value: 1e-08
+add_cross_attention:
+    value: false
+apply_spec_augment:
+    value: false
+architectures:
+    value:
+        - WhisperForConditionalGeneration
+attention_dropout:
+    value: 0
+auto_find_batch_size:
+    value: false
+average_tokens_across_devices:
+    value: false
+bad_words_ids:
+    value: null
+batch_eval_metrics:
+    value: false
+begin_suppress_tokens:
+    value:
+        - 220
+        - 50257
+bf16:
+    value: false
+bf16_full_eval:
+    value: false
+bos_token_id:
+    value: 50257
+chunk_size_feed_forward:
+    value: 0
+classifier_proj_size:
+    value: 256
+cross_attention_hidden_size:
+    value: null
+d_model:
+    value: 768
+data_seed:
+    value: null
+dataloader_drop_last:
+    value: false
+dataloader_num_workers:
+    value: 0
+dataloader_persistent_workers:
+    value: false
+dataloader_pin_memory:
+    value: true
+dataloader_prefetch_factor:
+    value: null
+ddp_backend:
+    value: null
+ddp_broadcast_buffers:
+    value: null
+ddp_bucket_cap_mb:
+    value: null
+ddp_find_unused_parameters:
+    value: null
+ddp_timeout:
+    value: 1800
+debug:
+    value: []
+decoder_attention_heads:
+    value: 12
+decoder_ffn_dim:
+    value: 3072
+decoder_layerdrop:
+    value: 0
+decoder_layers:
+    value: 12
+decoder_start_token_id:
+    value: 50258
+deepspeed:
+    value: null
+disable_tqdm:
+    value: false
+dispatch_batches:
+    value: null
+diversity_penalty:
+    value: 0
+do_eval:
+    value: true
+do_predict:
+    value: false
+do_sample:
+    value: false
+do_train:
+    value: true
+dropout:
+    value: 0
+early_stopping:
+    value: false
+encoder_attention_heads:
+    value: 12
+encoder_ffn_dim:
+    value: 3072
+encoder_layerdrop:
+    value: 0
+encoder_layers:
+    value: 12
+encoder_no_repeat_ngram_size:
+    value: 0
+eos_token_id:
+    value: 50257
+eval_accumulation_steps:
+    value: null
+eval_delay:
+    value: 0
+eval_do_concat_batches:
+    value: true
+eval_on_start:
+    value: false
+eval_steps:
+    value: 1000
+eval_strategy:
+    value: steps
+eval_use_gather_object:
+    value: false
+evaluation_strategy:
+    value: steps
+exponential_decay_length_penalty:
+    value: null
+finetuning_task:
+    value: null
+forced_bos_token_id:
+    value: null
+forced_decoder_ids:
+    value: null
+forced_eos_token_id:
+    value: null
+fp16:
+    value: true
+fp16_backend:
+    value: auto
+fp16_full_eval:
+    value: false
+fp16_opt_level:
+    value: O1
+fsdp:
+    value: []
+fsdp_config:
+    value:
+        min_num_params: 0
+        xla: false
+        xla_fsdp_grad_ckpt: false
+        xla_fsdp_v2: false
+fsdp_min_num_params:
+    value: 0
+fsdp_transformer_layer_cls_to_wrap:
+    value: null
+full_determinism:
+    value: false
+generation_config:
+    value: null
+generation_max_length:
+    value: 225
+generation_num_beams:
+    value: null
+gradient_accumulation_steps:
+    value: 1
+gradient_checkpointing:
+    value: true
+gradient_checkpointing_kwargs:
+    value: null
+greater_is_better:
+    value: false
+group_by_length:
+    value: false
+half_precision_backend:
+    value: auto
+hub_always_push:
+    value: false
+hub_model_id:
+    value: null
+hub_private_repo:
+    value: null
+hub_strategy:
+    value: every_save
+hub_token:
+    value: <HUB_TOKEN>
+id2label:
+    value:
+        "0": LABEL_0
+        "1": LABEL_1
+ignore_data_skip:
+    value: false
+include_for_metrics:
+    value: []
+include_inputs_for_metrics:
+    value: false
+include_num_input_tokens_seen:
+    value: false
+include_tokens_per_second:
+    value: false
+init_std:
+    value: 0.02
+is_decoder:
+    value: false
+is_encoder_decoder:
+    value: true
+jit_mode_eval:
+    value: false
+label_names:
+    value: null
+label_smoothing_factor:
+    value: 0
+label2id:
+    value:
+        LABEL_0: 0
+        LABEL_1: 1
+learning_rate:
+    value: 1e-05
+length_column_name:
+    value: input_length
+length_penalty:
+    value: 1
+load_best_model_at_end:
+    value: true
+local_rank:
+    value: 0
+log_level:
+    value: passive
+log_level_replica:
+    value: warning
+log_on_each_node:
+    value: true
+logging_dir:
+    value: ./runs/Feb12_12-58-59_tknika
+logging_first_step:
+    value: false
+logging_nan_inf_filter:
+    value: true
+logging_steps:
+    value: 25
+logging_strategy:
+    value: steps
+lr_scheduler_type:
+    value: linear
+mask_feature_length:
+    value: 10
+mask_feature_min_masks:
+    value: 0
+mask_feature_prob:
+    value: 0
+mask_time_length:
+    value: 10
+mask_time_min_masks:
+    value: 2
+mask_time_prob:
+    value: 0.05
+max_grad_norm:
+    value: 1
+max_length:
+    value: 448
+max_source_positions:
+    value: 1500
+max_steps:
+    value: 8000
+max_target_positions:
+    value: 448
+median_filter_width:
+    value: 7
+metric_for_best_model:
+    value: wer
+min_length:
+    value: 0
+model/num_parameters:
+    value: 241734912
+model_type:
+    value: whisper
+mp_parameters:
+    value: ""
+neftune_noise_alpha:
+    value: null
+no_cuda:
+    value: false
+no_repeat_ngram_size:
+    value: 0
+num_beam_groups:
+    value: 1
+num_beams:
+    value: 1
+num_hidden_layers:
+    value: 12
+num_mel_bins:
+    value: 80
+num_return_sequences:
+    value: 1
+num_train_epochs:
+    value: 3
+optim:
+    value: adamw_torch
+optim_args:
+    value: null
+optim_target_modules:
+    value: null
+output_attentions:
+    value: false
+output_dir:
+    value: ./
+output_hidden_states:
+    value: false
+output_scores:
+    value: false
+overwrite_output_dir:
+    value: true
+pad_token_id:
+    value: 50257
+past_index:
+    value: -1
+per_device_eval_batch_size:
+    value: 16
+per_device_train_batch_size:
+    value: 32
+per_gpu_eval_batch_size:
+    value: null
+per_gpu_train_batch_size:
+    value: null
+predict_with_generate:
+    value: true
+prediction_loss_only:
+    value: false
+prefix:
+    value: null
+problem_type:
+    value: null
+push_to_hub:
+    value: true
+push_to_hub_model_id:
+    value: null
+push_to_hub_organization:
+    value: null
+push_to_hub_token:
+    value: <PUSH_TO_HUB_TOKEN>
+ray_scope:
+    value: last
+remove_invalid_values:
+    value: false
+remove_unused_columns:
+    value: true
+repetition_penalty:
+    value: 1
+report_to:
+    value:
+        - wandb
+restore_callback_states_from_checkpoint:
+    value: false
+resume_from_checkpoint:
+    value: null
+return_dict:
+    value: true
+return_dict_in_generate:
+    value: false
+run_name:
+    value: whisper-small-eu
+save_on_each_node:
+    value: false
+save_only_model:
+    value: false
+save_safetensors:
+    value: true
+save_steps:
+    value: 1000
+save_strategy:
+    value: steps
+save_total_limit:
+    value: null
+scale_embedding:
+    value: false
+seed:
+    value: 42
+sep_token_id:
+    value: null
+skip_memory_metrics:
+    value: true
+sortish_sampler:
+    value: false
+split_batches:
+    value: null
+suppress_tokens:
+    value: null
+task_specific_params:
+    value: null
+temperature:
+    value: 1
+tf_legacy_loss:
+    value: false
+tf32:
+    value: null
+tie_encoder_decoder:
+    value: false
+tie_word_embeddings:
+    value: true
+tokenizer_class:
+    value: null
+top_k:
+    value: 50
+top_p:
+    value: 1
+torch_compile:
+    value: false
+torch_compile_backend:
+    value: null
+torch_compile_mode:
+    value: null
+torch_dtype:
+    value: float32
+torch_empty_cache_steps:
+    value: null
+torchdynamo:
+    value: null
+torchscript:
+    value: false
+tpu_metrics_debug:
+    value: false
+tpu_num_cores:
+    value: null
+transformers_version:
+    value: 4.49.0.dev0
+typical_p:
+    value: 1
+use_bfloat16:
+    value: false
+use_cache:
+    value: false
+use_cpu:
+    value: false
+use_ipex:
+    value: false
+use_legacy_prediction_loop:
+    value: false
+use_liger_kernel:
+    value: false
+use_mps_device:
+    value: false
+use_weighted_layer_sum:
+    value: false
+vocab_size:
+    value: 51865
+warmup_ratio:
+    value: 0
+warmup_steps:
+    value: 500
+weight_decay:
+    value: 0