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--- |
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base_model: distil-whisper/distil-large-v3 |
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datasets: |
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- Gabi00/english-mistakes |
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language: |
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- eng |
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library_name: peft |
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license: apache-2.0 |
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metrics: |
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- wer |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: Whisper Small Eng - Gabriel Mora |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: English-mistakes |
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type: Gabi00/english-mistakes |
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config: default |
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split: validation |
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args: 'config: eng, split: test' |
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metrics: |
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- type: wer |
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value: 18.233650721249788 |
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name: Wer |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Whisper Small Eng - Gabriel Mora |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co./openai/whisper-small) on the English-mistakes dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6550 |
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- Wer: 18.2337 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 28 |
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- eval_batch_size: 28 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 50 |
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- training_steps: 100000 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:------:|:-----:|:---------------:|:-------:| |
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| 1.5085 | 0.4444 | 500 | 1.1844 | 25.9507 | |
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| 1.1717 | 0.8889 | 1000 | 0.9522 | 25.2751 | |
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| 1.1302 | 1.3333 | 1500 | 0.8634 | 22.0879 | |
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| 1.0094 | 1.7778 | 2000 | 0.8098 | 21.0103 | |
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| 1.0509 | 2.2222 | 2500 | 0.7784 | 23.2054 | |
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| 0.9722 | 2.6667 | 3000 | 0.7555 | 21.5206 | |
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| 0.9562 | 3.1111 | 3500 | 0.7401 | 21.0075 | |
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| 0.9995 | 3.5556 | 4000 | 0.7269 | 19.8985 | |
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| 0.9497 | 4.0 | 4500 | 0.7170 | 19.3626 | |
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| 0.8703 | 4.4444 | 5000 | 0.7078 | 19.4652 | |
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| 1.0015 | 4.8889 | 5500 | 0.7004 | 20.1608 | |
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| 0.9248 | 5.3333 | 6000 | 0.6947 | 17.7034 | |
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| 0.9163 | 5.7778 | 6500 | 0.6880 | 17.4953 | |
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| 0.8833 | 6.2222 | 7000 | 0.6823 | 17.4668 | |
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| 0.9051 | 6.6667 | 7500 | 0.6770 | 17.4554 | |
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| 0.8882 | 7.1111 | 8000 | 0.6730 | 17.3613 | |
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| 0.8879 | 7.5556 | 8500 | 0.6684 | 18.3220 | |
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| 0.8396 | 8.0 | 9000 | 0.6647 | 18.2165 | |
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| 0.9282 | 8.4444 | 9500 | 0.6616 | 18.4646 | |
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| 0.8581 | 8.8889 | 10000 | 0.6578 | 18.1538 | |
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| 0.8938 | 9.3333 | 10500 | 0.6550 | 18.2337 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.42.3 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
