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--- |
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license: apache-2.0 |
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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: openai/whisper-large-v2 |
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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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# openai/whisper-large-v2 |
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This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7993 |
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- Wer: 21.2788 |
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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: 4 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 4 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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- total_eval_batch_size: 16 |
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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: 400 |
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- training_steps: 800 |
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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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| 0.007 | 8.33 | 100 | 0.5728 | 21.4885 | |
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| 0.0007 | 16.67 | 200 | 0.7017 | 22.1174 | |
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| 0.0003 | 25.0 | 300 | 0.7358 | 21.5933 | |
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| 0.0002 | 33.33 | 400 | 0.7598 | 21.5933 | |
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| 0.0002 | 41.67 | 500 | 0.7793 | 22.0126 | |
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| 0.0001 | 50.0 | 600 | 0.7896 | 22.0126 | |
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| 0.0001 | 58.33 | 700 | 0.7969 | 21.2788 | |
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| 0.0001 | 66.67 | 800 | 0.7993 | 21.2788 | |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.13.1 |
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- Datasets 2.8.1.dev0 |
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- Tokenizers 0.13.2 |
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