| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - wer |
| model-index: |
| - name: whisper-base |
| 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-base |
|
|
| This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2522 |
| - Wer: 23.1797 |
|
|
| ## 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: 64 |
| - eval_batch_size: 64 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 500 |
| - training_steps: 10000 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:-----:|:-----:|:---------------:|:-------:| |
| | 2.1114 | 0.0 | 1 | 2.3698 | 75.1864 | |
| | 0.3272 | 0.29 | 1000 | 0.4182 | 37.7505 | |
| | 0.251 | 0.58 | 2000 | 0.3408 | 30.9679 | |
| | 0.2207 | 0.88 | 3000 | 0.3059 | 28.3058 | |
| | 0.1779 | 1.17 | 4000 | 0.2890 | 26.7555 | |
| | 0.1691 | 1.46 | 5000 | 0.2742 | 25.2099 | |
| | 0.1622 | 1.75 | 6000 | 0.2645 | 24.6840 | |
| | 0.1397 | 2.04 | 7000 | 0.2587 | 23.8812 | |
| | 0.1394 | 2.34 | 8000 | 0.2562 | 23.6586 | |
| | 0.1361 | 2.63 | 9000 | 0.2536 | 23.4633 | |
| | 0.1356 | 2.92 | 10000 | 0.2522 | 23.1797 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.27.4 |
| - Pytorch 2.0.0 |
| - Datasets 2.11.0 |
| - Tokenizers 0.13.3 |
| |
