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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-us_en_bs128 |
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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: 0.3417945690672963 |
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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-us_en_bs128 |
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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: 0.8372 |
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- Wer Ortho: 0.3399 |
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- Wer: 0.3418 |
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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: 0.0001 |
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- train_batch_size: 128 |
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- eval_batch_size: 128 |
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- seed: 42 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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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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| 0.1633 | 6.25 | 25 | 0.5503 | 0.3177 | 0.3164 | |
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| 0.0027 | 12.5 | 50 | 0.6676 | 0.3288 | 0.3294 | |
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| 0.0011 | 18.75 | 75 | 0.7095 | 0.3134 | 0.3182 | |
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| 0.0012 | 25.0 | 100 | 0.7296 | 0.3196 | 0.3176 | |
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| 0.0014 | 31.25 | 125 | 0.7460 | 0.3541 | 0.3583 | |
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| 0.005 | 37.5 | 150 | 0.7059 | 0.4405 | 0.4610 | |
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| 0.0009 | 43.75 | 175 | 0.7803 | 0.3924 | 0.3961 | |
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| 0.0004 | 50.0 | 200 | 0.7996 | 0.3455 | 0.3512 | |
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| 0.0001 | 56.25 | 225 | 0.8074 | 0.3411 | 0.3442 | |
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| 0.0001 | 62.5 | 250 | 0.8146 | 0.3424 | 0.3459 | |
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| 0.0001 | 68.75 | 275 | 0.8197 | 0.3430 | 0.3459 | |
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| 0.0001 | 75.0 | 300 | 0.8239 | 0.3399 | 0.3424 | |
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| 0.0001 | 81.25 | 325 | 0.8274 | 0.3374 | 0.3400 | |
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| 0.0001 | 87.5 | 350 | 0.8303 | 0.3356 | 0.3383 | |
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| 0.0001 | 93.75 | 375 | 0.8324 | 0.3368 | 0.3400 | |
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| 0.0001 | 100.0 | 400 | 0.8341 | 0.3368 | 0.3388 | |
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| 0.0001 | 106.25 | 425 | 0.8354 | 0.3405 | 0.3424 | |
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| 0.0001 | 112.5 | 450 | 0.8364 | 0.3399 | 0.3418 | |
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| 0.0001 | 118.75 | 475 | 0.8371 | 0.3399 | 0.3418 | |
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| 0.0001 | 125.0 | 500 | 0.8372 | 0.3399 | 0.3418 | |
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### Framework versions |
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- Transformers 4.46.2 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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