| --- |
| 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 v2 dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.4081 |
| - Wer: 17.4837 |
|
|
| ## 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 | 0.8951 | 40.3595 | |
| | 0.6363 | 2.0 | 44 | 0.5120 | 25.1634 | |
| | 0.2988 | 3.0 | 66 | 0.4660 | 20.4248 | |
| | 0.2174 | 4.0 | 88 | 0.4379 | 36.7647 | |
| | 0.1602 | 5.0 | 110 | 0.4227 | 44.9346 | |
| | 0.1294 | 6.0 | 132 | 0.4130 | 18.6275 | |
| | 0.0972 | 7.0 | 154 | 0.4207 | 18.1373 | |
| | 0.0591 | 8.0 | 176 | 0.4045 | 19.4444 | |
| | 0.0377 | 9.0 | 198 | 0.4233 | 15.6863 | |
| | 0.0337 | 10.0 | 220 | 0.4078 | 17.1569 | |
| | 0.0292 | 11.0 | 242 | 0.4063 | 17.6471 | |
| | 0.0225 | 12.0 | 264 | 0.4063 | 16.9935 | |
| | 0.0313 | 13.0 | 286 | 0.4073 | 17.4837 | |
| | 0.0185 | 14.0 | 308 | 0.4080 | 17.4837 | |
| | 0.0198 | 15.0 | 330 | 0.4081 | 17.4837 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.57.3 |
| - Pytorch 2.9.1+cu130 |
| - Datasets 4.4.2 |
| - Tokenizers 0.22.2 |
| |
