| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: openai/whisper-base |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: whisper-base-v4 |
| 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-v4 |
|
|
| 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: |
| - eval_loss: 2.6242 |
| - eval_wer: 90.4248 |
| - eval_runtime: 99.7998 |
| - eval_samples_per_second: 2.004 |
| - eval_steps_per_second: 0.251 |
| - epoch: 20.0 |
| - step: 1000 |
| |
| ## 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: 0.0001 |
| - train_batch_size: 16 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 500 |
| - training_steps: 2000 |
| - mixed_precision_training: Native AMP |
|
|
| ### Framework versions |
|
|
| - Transformers 4.46.2 |
| - Pytorch 2.5.0+cu121 |
| - Datasets 3.1.0 |
| - Tokenizers 0.20.3 |
|
|
