| --- |
| library_name: transformers |
| language: |
| - fr |
| license: apache-2.0 |
| base_model: openai/whisper-small |
| tags: |
| - generated_from_trainer |
| metrics: |
| - wer |
| model-index: |
| - name: 52Hz Small Fr - IMT Atlantique X 52 Hertz |
| 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. --> |
|
|
| # 52Hz Small Fr - IMT Atlantique X 52 Hertz |
|
|
| This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Transcriptions IMTx52Hz v3 dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.4065 |
| - Wer: 17.8105 |
|
|
| ## 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: 2e-05 |
| - train_batch_size: 4 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 16 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 15 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:-----:|:----:|:---------------:|:-------:| |
| | 1.4611 | 1.0 | 22 | 0.8947 | 39.8693 | |
| | 0.6451 | 2.0 | 44 | 0.5211 | 25.4902 | |
| | 0.3082 | 3.0 | 66 | 0.4803 | 20.4248 | |
| | 0.224 | 4.0 | 88 | 0.4255 | 37.7451 | |
| | 0.1531 | 5.0 | 110 | 0.4062 | 17.9739 | |
| | 0.1294 | 6.0 | 132 | 0.4146 | 19.1176 | |
| | 0.1018 | 7.0 | 154 | 0.4123 | 19.6078 | |
| | 0.0546 | 8.0 | 176 | 0.4034 | 20.2614 | |
| | 0.0401 | 9.0 | 198 | 0.4386 | 17.3203 | |
| | 0.0476 | 10.0 | 220 | 0.4225 | 18.6275 | |
| | 0.0261 | 11.0 | 242 | 0.4131 | 18.4641 | |
| | 0.0226 | 12.0 | 264 | 0.4035 | 17.8105 | |
| | 0.0323 | 13.0 | 286 | 0.4050 | 17.6471 | |
| | 0.0208 | 14.0 | 308 | 0.4064 | 17.8105 | |
| | 0.0189 | 15.0 | 330 | 0.4065 | 17.8105 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.57.3 |
| - Pytorch 2.9.1+cu130 |
| - Datasets 4.4.2 |
| - Tokenizers 0.22.2 |
| |
