| --- |
| library_name: transformers |
| language: |
| - fr |
| license: apache-2.0 |
| base_model: StephaneBah/whisper-small-rad-fr1.1 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - wer |
| model-index: |
| - name: Whisper Small Fr - Radiologie2.0 Encoder-Layer[0:3]+ LoRa(QKVO; FFN) |
| 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 Small Fr - Radiologie2.0 Encoder-Layer[0:3]+ LoRa(QKVO; FFN) |
|
|
| This model is a fine-tuned version of [StephaneBah/whisper-small-rad-fr1.1](https://huggingface.co/StephaneBah/whisper-small-rad-fr1.1) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.8256 |
| - Wer: 34.6130 |
|
|
| ## 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-05 |
| - train_batch_size: 8 |
| - eval_batch_size: 6 |
| - seed: 3407 |
| - optimizer: Use OptimizerNames.ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - training_steps: 1000 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:-----:|:----:|:---------------:|:-------:| |
| | No log | 6.25 | 100 | 0.8140 | 34.4912 | |
| | No log | 12.5 | 200 | 0.8138 | 34.4912 | |
| | No log | 18.75 | 300 | 0.8165 | 34.4912 | |
| | No log | 25.0 | 400 | 0.8190 | 34.4302 | |
| | 0.0001 | 31.25 | 500 | 0.8202 | 34.5521 | |
| | 0.0001 | 37.5 | 600 | 0.8234 | 34.4302 | |
| | 0.0001 | 43.75 | 700 | 0.8248 | 34.4302 | |
| | 0.0001 | 50.0 | 800 | 0.8261 | 34.2474 | |
| | 0.0001 | 56.25 | 900 | 0.8266 | 34.6740 | |
| | 0.0 | 62.5 | 1000 | 0.8256 | 34.6130 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.51.3 |
| - Pytorch 2.6.0+cu124 |
| - Datasets 3.6.0 |
| - Tokenizers 0.21.2 |
|
|
