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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: openai/whisper-tiny |
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tags: |
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- generated_from_trainer |
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datasets: |
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- PolyAI/minds14 |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-tiny-en-US |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: PolyAI/minds14 |
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type: PolyAI/minds14 |
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config: en-US |
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split: train[450:] |
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args: en-US |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.34887839433293977 |
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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-tiny-en-US |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the PolyAI/minds14 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6638 |
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- Wer Ortho: 34.5466 |
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- Wer: 0.3489 |
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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: 16 |
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- eval_batch_size: 16 |
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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: constant_with_warmup |
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- lr_scheduler_warmup_steps: 50 |
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- training_steps: 500 |
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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 Ortho | Wer | |
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|:-------------:|:-------:|:----:|:---------------:|:---------:|:------:| |
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| 0.7657 | 1.7857 | 50 | 0.5870 | 39.4818 | 0.3932 | |
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| 0.2562 | 3.5714 | 100 | 0.4866 | 34.8550 | 0.3483 | |
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| 0.0666 | 5.3571 | 150 | 0.5190 | 34.5466 | 0.3489 | |
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| 0.0228 | 7.1429 | 200 | 0.5649 | 32.4491 | 0.3288 | |
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| 0.0065 | 8.9286 | 250 | 0.5845 | 32.0173 | 0.3229 | |
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| 0.0018 | 10.7143 | 300 | 0.6142 | 33.6212 | 0.3400 | |
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| 0.0012 | 12.5 | 350 | 0.6320 | 33.3128 | 0.3371 | |
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| 0.0008 | 14.2857 | 400 | 0.6443 | 34.1764 | 0.3465 | |
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| 0.0007 | 16.0714 | 450 | 0.6548 | 34.2381 | 0.3447 | |
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| 0.0007 | 17.8571 | 500 | 0.6638 | 34.5466 | 0.3489 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
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