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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: biodatlab/whisper-th-medium-combined |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: outs |
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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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# outs |
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This model is a fine-tuned version of [biodatlab/whisper-th-medium-combined](https://huggingface.co/biodatlab/whisper-th-medium-combined) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0878 |
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- Cer: 5.4469 |
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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: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine_with_restarts |
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- lr_scheduler_warmup_steps: 5000 |
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- num_epochs: 15.0 |
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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 | Cer | |
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|:-------------:|:-------:|:----:|:---------------:|:------:| |
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| 0.0275 | 0.9926 | 67 | 0.0804 | 4.9648 | |
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| 0.0359 | 2.0 | 135 | 0.0807 | 6.0688 | |
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| 0.0317 | 2.9926 | 202 | 0.0813 | 5.8626 | |
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| 0.0196 | 4.0 | 270 | 0.0819 | 4.9681 | |
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| 0.021 | 4.9926 | 337 | 0.0823 | 4.8683 | |
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| 0.0209 | 6.0 | 405 | 0.0831 | 4.8783 | |
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| 0.0223 | 6.9926 | 472 | 0.0866 | 5.0080 | |
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| 0.0173 | 8.0 | 540 | 0.0864 | 5.2541 | |
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| 0.0231 | 8.9926 | 607 | 0.0839 | 4.6422 | |
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| 0.0131 | 10.0 | 675 | 0.0860 | 5.3405 | |
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| 0.0134 | 10.9926 | 742 | 0.0899 | 5.2674 | |
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| 0.0183 | 12.0 | 810 | 0.0873 | 5.8094 | |
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| 0.0172 | 12.9926 | 877 | 0.0893 | 4.9215 | |
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| 0.0178 | 14.0 | 945 | 0.0855 | 5.7096 | |
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| 0.0127 | 14.8889 | 1005 | 0.0878 | 5.4469 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.1 |
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- Tokenizers 0.19.1 |
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