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language: |
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- en |
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license: apache-2.0 |
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base_model: openai/whisper-large-v3 |
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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-v3-cit-do015-wd0-lr3e-06-FULL |
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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-v3-cit-do015-wd0-lr3e-06-FULL |
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This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co./openai/whisper-large-v3) on the FULL dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5117 |
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- Wer Ortho: 27.7362 |
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- Wer: 18.6050 |
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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: 3e-06 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 4 |
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- total_train_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: 100 |
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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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| 0.9582 | 0.4773 | 50 | 0.6479 | 34.9922 | 25.6303 | |
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| 0.6764 | 0.9547 | 100 | 0.5605 | 30.9901 | 21.5126 | |
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| 0.5263 | 1.4320 | 150 | 0.5337 | 29.3892 | 20.0168 | |
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| 0.5084 | 1.9093 | 200 | 0.5186 | 28.0842 | 19.1261 | |
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| 0.4226 | 2.3866 | 250 | 0.5132 | 27.9624 | 18.8571 | |
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| 0.4078 | 2.8640 | 300 | 0.5083 | 28.1538 | 19.0420 | |
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| 0.3775 | 3.3413 | 350 | 0.5083 | 28.3974 | 18.8403 | |
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| 0.3532 | 3.8186 | 400 | 0.5093 | 28.1538 | 18.6555 | |
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| 0.3359 | 4.2959 | 450 | 0.5098 | 27.7188 | 18.5210 | |
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| 0.3189 | 4.7733 | 500 | 0.5117 | 27.7362 | 18.6050 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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