transformers safetensors whisper automatic-speech-recognition generated_from_trainer base_model:bofenghuang/whisper-large-v3-french-distil-dec16 license:mit endpoints_compatible region:us
---
license: mit
base_model: bofenghuang/whisper-large-v3-french-distil-dec16
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper
  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

This model is a fine-tuned version of [bofenghuang/whisper-large-v3-french-distil-dec16](https://huggingface.co/bofenghuang/whisper-large-v3-french-distil-dec16) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1122
- Wer: 5.3589

## 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: 5e-06
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 20
- training_steps: 200

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.4042        | 0.38  | 20   | 0.2881          | 4.5501 |
| 0.3463        | 0.77  | 40   | 0.2060          | 4.3478 |
| 0.125         | 1.15  | 60   | 0.1498          | 4.7523 |
| 0.0606        | 1.54  | 80   | 0.1154          | 4.3478 |
| 0.0884        | 1.92  | 100  | 0.1026          | 4.8534 |
| 0.0189        | 2.31  | 120  | 0.0995          | 4.8534 |
| 0.0235        | 2.69  | 140  | 0.1085          | 4.6512 |
| 0.0126        | 3.08  | 160  | 0.1100          | 4.6512 |
| 0.0096        | 3.46  | 180  | 0.1114          | 5.2578 |
| 0.0214        | 3.85  | 200  | 0.1122          | 5.3589 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1
