| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: openai/whisper-large-v3 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - wer |
| | model-index: |
| | - name: ap-vIPVV9dqluiiO2kf7JwA61 |
| | 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. --> |
| |
|
| | # ap-vIPVV9dqluiiO2kf7JwA61 |
| |
|
| | This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.3485 |
| | - Model Preparation Time: 0.0151 |
| | - Wer: 0.1102 |
| |
|
| | ## 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: 3e-06 |
| | - train_batch_size: 8 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 8 |
| | - total_train_batch_size: 64 |
| | - optimizer: Use OptimizerNames.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: 400 |
| | - num_epochs: 10 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Wer | |
| | |:-------------:|:------:|:----:|:---------------:|:----------------------:|:------:| |
| | | 0.742 | 0.9791 | 41 | 0.7811 | 0.0151 | 0.1875 | |
| | | 0.5242 | 1.9791 | 82 | 0.5559 | 0.0151 | 0.1543 | |
| | | 0.328 | 2.9791 | 123 | 0.3325 | 0.0151 | 0.1214 | |
| | | 0.2466 | 3.9791 | 164 | 0.2946 | 0.0151 | 0.1120 | |
| | | 0.2118 | 4.9791 | 205 | 0.2802 | 0.0151 | 0.1094 | |
| | | 0.1682 | 5.9791 | 246 | 0.2751 | 0.0151 | 0.1052 | |
| | | 0.1316 | 6.9791 | 287 | 0.2780 | 0.0151 | 0.1070 | |
| | | 0.0857 | 7.9791 | 328 | 0.3017 | 0.0151 | 0.1058 | |
| | | 0.0725 | 8.9791 | 369 | 0.3152 | 0.0151 | 0.1060 | |
| | | 0.0448 | 9.9791 | 410 | 0.3485 | 0.0151 | 0.1102 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.48.3 |
| | - Pytorch 2.5.1+cu124 |
| | - Datasets 3.2.0 |
| | - Tokenizers 0.21.0 |
| |
|
