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alignment-score-model

Text Classification
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xlm-roberta
Generated from Trainer
text-embeddings-inference
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  1. README.md +10 -11
  2. final/model.safetensors +1 -1
  3. final/training_args.bin +1 -1
  4. model.safetensors +1 -1
  5. runs/Sep14_18-21-05_fs-cai-002/events.out.tfevents.1757874070.fs-cai-002.3616333.0 +2 -2
README.md CHANGED
@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [intfloat/multilingual-e5-base](https://huggingface.co/intfloat/multilingual-e5-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0120
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- - Precision: 0.9989
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- - Recall: 0.9989
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- - F1 Macro: 0.9989
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- - Accuracy: 0.9989
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  ## Model description
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@@ -43,7 +43,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 3e-05
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  - train_batch_size: 32
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  - eval_batch_size: 128
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  - seed: 0
@@ -53,16 +53,15 @@ The following hyperparameters were used during training:
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  - total_eval_batch_size: 1024
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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- - num_epochs: 3
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 Macro | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|:--------:|
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- | No log | 0 | 0 | 0.6272 | 0.2550 | 0.5 | 0.3377 | 0.5100 |
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- | No log | 1.0 | 31 | 0.0226 | 0.9984 | 0.9984 | 0.9984 | 0.9984 |
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- | No log | 2.0 | 62 | 0.0141 | 0.9989 | 0.9989 | 0.9989 | 0.9989 |
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- | No log | 3.0 | 93 | 0.0120 | 0.9989 | 0.9989 | 0.9989 | 0.9989 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [intfloat/multilingual-e5-base](https://huggingface.co/intfloat/multilingual-e5-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3028
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+ - Precision: 0.7442
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+ - Recall: 0.5171
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+ - F1 Macro: 0.3753
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+ - Accuracy: 0.5267
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 3e-06
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  - train_batch_size: 32
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  - eval_batch_size: 128
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  - seed: 0
 
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  - total_eval_batch_size: 1024
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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+ - num_epochs: 2
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 Macro | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|:--------:|
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+ | No log | 0 | 0 | 0.6188 | 0.2550 | 0.5 | 0.3377 | 0.5100 |
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+ | No log | 1.0 | 31 | 0.3472 | 0.7553 | 0.5011 | 0.3402 | 0.5110 |
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+ | No log | 2.0 | 62 | 0.3028 | 0.7442 | 0.5171 | 0.3753 | 0.5267 |
 
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  ### Framework versions
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