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README.md

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+---
+language:
+- en
+metrics:
+- wer
+base_model:
+- openai/whisper-small
+tags:
+- whisper
+- stt
+- speech-to-text
+- speech
+- automatic-speech-recognition
+- fine-tuned
+---
+# Whisper Small Atc 5S
+
+Fine-tuned Whisper model based on [openai/whisper-small](https://huggingface.co/openai/whisper-small).
+
+## Training Results
+
+| Metric | Base Model | Fine-tuned |
+|--------|------------|------------|
+| WER    | 55.54% | 69.23% |
+
+**Note:** WER increased by 13.69% compared to base model
+
+## Training Details
+
+- **Base Model:** [openai/whisper-small](https://huggingface.co/openai/whisper-small)
+- **Training Dataset:** [Trelis/atc-train-1gb-5s](https://huggingface.co/datasets/Trelis/atc-train-1gb-5s)
+- **Train Loss:** 0.3593
+- **Training Time:** 3.6 minutes
+
+## Inference
+
+```python
+from transformers import pipeline
+
+asr = pipeline("automatic-speech-recognition", model="Trelis/whisper-small-atc-5s")
+result = asr("path/to/audio.wav")
+print(result["text"])
+```
+
+## Training Logs
+
+Full training logs are available in [training_log.txt](training_log.txt).
+
+---
+*Fine-tuned using [Trelis Studio](https://studio.trelis.com)*