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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: 0.35360094451003543 |
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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: 0.6166 |
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- Wer Ortho: 0.3504 |
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- Wer: 0.3536 |
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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: linear |
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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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| 0.7658 | 1.7857 | 50 | 0.5871 | 0.3948 | 0.3932 | |
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| 0.2602 | 3.5714 | 100 | 0.4866 | 0.3504 | 0.3501 | |
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| 0.0796 | 5.3571 | 150 | 0.5121 | 0.3424 | 0.3453 | |
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| 0.0316 | 7.1429 | 200 | 0.5443 | 0.3374 | 0.3418 | |
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| 0.0116 | 8.9286 | 250 | 0.5672 | 0.3202 | 0.3253 | |
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| 0.0034 | 10.7143 | 300 | 0.5966 | 0.3529 | 0.3566 | |
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| 0.0026 | 12.5 | 350 | 0.6046 | 0.3541 | 0.3583 | |
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| 0.002 | 14.2857 | 400 | 0.6098 | 0.3498 | 0.3536 | |
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| 0.002 | 16.0714 | 450 | 0.6146 | 0.3510 | 0.3542 | |
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| 0.002 | 17.8571 | 500 | 0.6166 | 0.3504 | 0.3536 | |
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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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