| --- |
| license: apache-2.0 |
| base_model: openai/whisper-medium |
| tags: |
| - generated_from_trainer |
| metrics: |
| - wer |
| model-index: |
| - name: whisper_medium |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # whisper_medium |
| |
| This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.8150 |
| - Cer: 18.5268 |
| - Wer: 29.2412 |
| |
| ## Model description |
| |
| More information needed |
| |
| ## Intended uses & limitations |
| |
| More information needed |
| |
| ## Training and evaluation data |
| |
| More information needed |
| |
| ## Training procedure |
| |
| ### Training hyperparameters |
| |
| The following hyperparameters were used during training: |
| - learning_rate: 1e-05 |
| - train_batch_size: 4 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 8 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 1000 |
| - num_epochs: 16 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Cer | Validation Loss | Wer | |
| |:-------------:|:-------:|:-----:|:-------:|:---------------:|:-------:| |
| | 1.2907 | 0.9999 | 4710 | 23.0132 | 0.7406 | 36.5517 | |
| | 0.7187 | 2.0 | 9421 | 20.8767 | 0.7060 | 33.3982 | |
| | 0.6 | 2.9997 | 14130 | 19.9648 | 0.6988 | 31.7264 | |
| | 0.5865 | 3.9999 | 18840 | 20.0014 | 0.7123 | 31.6218 | |
| | 0.5186 | 5.0 | 23551 | 19.2677 | 0.7172 | 30.4461 | |
| | 0.472 | 5.9997 | 28260 | 18.9852 | 0.7162 | 30.0906 | |
| | 0.4797 | 6.9999 | 32970 | 19.3379 | 0.7248 | 30.4956 | |
| | 0.4354 | 8.0 | 37681 | 19.2062 | 0.7400 | 30.2514 | |
| | 0.4001 | 8.9999 | 42391 | 19.0646 | 0.7527 | 29.9263 | |
| | 0.3767 | 9.9996 | 47100 | 18.7777 | 0.7587 | 29.5899 | |
| | 0.3792 | 10.9999 | 51810 | 18.6863 | 0.7727 | 29.4977 | |
| | 0.3552 | 12.0 | 56521 | 18.5969 | 0.7830 | 29.4470 | |
| | 0.3371 | 12.9997 | 61230 | 18.6109 | 0.7887 | 29.4437 | |
| | 0.3418 | 13.9999 | 65940 | 0.7929 | 18.6870 | 29.5922 | |
| | 0.3225 | 15.0 | 70651 | 0.8090 | 18.6225 | 29.4099 | |
| | 0.3084 | 15.9997 | 75360 | 0.8150 | 18.5268 | 29.2412 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.41.2 |
| - Pytorch 2.1.2+cu118 |
| - Datasets 2.19.0 |
| - Tokenizers 0.19.1 |
| |
