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--- |
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library_name: transformers |
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language: |
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- sr |
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license: mit |
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base_model: openai/whisper-large-v3-turbo |
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tags: |
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- generated_from_trainer |
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datasets: |
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- espnet/yodas |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Large v3 Turbo Sr Test |
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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: Yodas |
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type: espnet/yodas |
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config: sr |
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split: None |
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args: sr |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.1377668019050979 |
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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 Large v3 Turbo Sr Test |
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### This model is in test phase DO NOT USE IT ... YET |
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This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the Yodas dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1195 |
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- Wer: 0.1378 |
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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: 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: 500 |
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- training_steps: 4000 |
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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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| 0.6455 | 0.2439 | 500 | 0.1869 | 0.1928 | |
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| 0.5858 | 0.4878 | 1000 | 0.1694 | 0.1870 | |
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| 0.5608 | 0.7317 | 1500 | 0.1507 | 0.1641 | |
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| 0.4547 | 0.9756 | 2000 | 0.1388 | 0.1542 | |
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| 0.3905 | 1.2195 | 2500 | 0.1341 | 0.1461 | |
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| 0.3857 | 1.4634 | 3000 | 0.1291 | 0.1450 | |
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| 0.3656 | 1.7073 | 3500 | 0.1243 | 0.1415 | |
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| 0.3369 | 1.9512 | 4000 | 0.1195 | 0.1378 | |
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### Framework versions |
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- Transformers 4.45.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.20.3 |
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