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--- |
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license: apache-2.0 |
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base_model: openai/whisper-large |
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tags: |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-medium-r22-e |
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results: [] |
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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-medium-r22-e |
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This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2567 |
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- Wer: 32.4317 |
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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: 5 |
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- training_steps: 150 |
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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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| 4.2827 | 0.02 | 10 | 2.4594 | 30.6262 | |
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| 1.5383 | 0.04 | 20 | 0.9529 | 36.0561 | |
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| 0.5967 | 0.05 | 30 | 0.4230 | 34.7607 | |
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| 0.3559 | 0.07 | 40 | 0.3960 | 33.9352 | |
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| 0.314 | 0.09 | 50 | 0.3285 | 32.7270 | |
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| 0.3339 | 0.11 | 60 | 0.3362 | 33.3244 | |
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| 0.3148 | 0.13 | 70 | 0.2927 | 31.6464 | |
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| 0.3128 | 0.14 | 80 | 0.2896 | 32.5458 | |
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| 0.3136 | 0.16 | 90 | 0.2828 | 32.8613 | |
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| 0.272 | 0.18 | 100 | 0.2818 | 33.9419 | |
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| 0.1936 | 0.2 | 110 | 0.2702 | 30.9148 | |
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| 0.2541 | 0.22 | 120 | 0.2644 | 31.8209 | |
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| 0.2957 | 0.23 | 130 | 0.2614 | 31.6531 | |
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| 0.2867 | 0.25 | 140 | 0.2574 | 31.6397 | |
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| 0.2085 | 0.27 | 150 | 0.2567 | 32.4317 | |
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### Framework versions |
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- Transformers 4.35.0.dev0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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