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--- |
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base_model: openai/whisper-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: 12.985346941102685 |
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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: 0.3644 |
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- Wer: 12.9853 |
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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: 8 |
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- eval_batch_size: 8 |
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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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- num_epochs: 3.0 |
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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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| 0.9139 | 0.1270 | 500 | 0.6388 | 24.1376 | |
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| 0.5572 | 0.2541 | 1000 | 0.4884 | 17.9087 | |
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| 0.5416 | 0.3811 | 1500 | 0.4371 | 15.2460 | |
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| 0.5542 | 0.5081 | 2000 | 0.4156 | 13.7921 | |
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| 0.6599 | 0.6352 | 2500 | 0.4036 | 13.4956 | |
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| 0.6117 | 0.7622 | 3000 | 0.3960 | 13.2676 | |
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| 0.5569 | 0.8892 | 3500 | 0.3890 | 13.1336 | |
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| 0.537 | 1.0163 | 4000 | 0.3850 | 12.5292 | |
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| 0.4677 | 1.1433 | 4500 | 0.3815 | 12.6261 | |
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| 0.5017 | 1.2703 | 5000 | 0.3792 | 12.4836 | |
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| 0.5346 | 1.3974 | 5500 | 0.3761 | 12.3126 | |
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| 0.4858 | 1.5244 | 6000 | 0.3735 | 12.2926 | |
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| 0.5478 | 1.6514 | 6500 | 0.3715 | 12.4009 | |
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| 0.5277 | 1.7785 | 7000 | 0.3699 | 12.2327 | |
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| 0.5153 | 1.9055 | 7500 | 0.3693 | 12.1643 | |
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| 0.5825 | 2.0325 | 8000 | 0.3681 | 12.1387 | |
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| 0.6049 | 2.1596 | 8500 | 0.3670 | 12.3211 | |
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| 0.5248 | 2.2866 | 9000 | 0.3662 | 12.1501 | |
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| 0.554 | 2.4136 | 9500 | 0.3653 | 12.0645 | |
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| 0.5031 | 2.5407 | 10000 | 0.3654 | 12.9312 | |
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| 0.5253 | 2.6677 | 10500 | 0.3647 | 12.9739 | |
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| 0.5132 | 2.7947 | 11000 | 0.3641 | 12.9511 | |
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| 0.5789 | 2.9217 | 11500 | 0.3644 | 12.9853 | |
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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 |
