---
library_name: peft
language:
- fr
license: apache-2.0
base_model: openai/whisper-small
tags:
- base_model:adapter:openai/whisper-small
- lora
- transformers
metrics:
- wer
model-index:
- name: Whisper Small Fr - IMT Atlantique X 52 Hertz Full
  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 - IMT Atlantique X 52 Hertz Full

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the FullDatabase dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6708
- Wer: 0.3327

## 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: 0.001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- 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: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 1.3574        | 0.4762 | 20   | 1.4124          | 0.3671 |
| 1.1555        | 0.9524 | 40   | 1.1674          | 0.3728 |
| 0.7839        | 1.4286 | 60   | 0.7497          | 0.3231 |
| 0.4459        | 1.9048 | 80   | 0.6860          | 0.3614 |
| 0.533         | 2.3810 | 100  | 0.6819          | 0.3461 |
| 0.2029        | 2.8571 | 120  | 0.6708          | 0.3327 |


### Framework versions

- PEFT 0.18.0
- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.4.1
- Tokenizers 0.22.1