---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-tiny-fr
  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-tiny-fr

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6094
- Model Preparation Time: 0.0026
- Wer: 0.3301
- Cer: 0.1774

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- training_steps: 33000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Model Preparation Time | Wer    | Cer    |
|:-------------:|:------:|:-----:|:---------------:|:----------------------:|:------:|:------:|
| 0.8933        | 0.0303 | 1000  | 1.3184          | 0.0026                 | 0.5726 | 0.3162 |
| 0.7455        | 0.0606 | 2000  | 1.1738          | 0.0026                 | 0.5533 | 0.2930 |
| 0.735         | 0.0909 | 3000  | 1.0462          | 0.0026                 | 0.6032 | 0.3290 |
| 0.6426        | 0.1212 | 4000  | 1.0629          | 0.0026                 | 0.4937 | 0.2473 |
| 0.6389        | 0.1515 | 5000  | 1.0132          | 0.0026                 | 0.5671 | 0.3415 |
| 0.532         | 0.1818 | 6000  | 1.0194          | 0.0026                 | 0.4639 | 0.2355 |
| 0.5341        | 0.2121 | 7000  | 1.0092          | 0.0026                 | 0.4619 | 0.2435 |
| 0.4773        | 0.2424 | 8000  | 0.9672          | 0.0026                 | 0.4666 | 0.2822 |
| 0.4932        | 0.2727 | 9000  | 0.9778          | 0.0026                 | 0.4175 | 0.2187 |
| 0.479         | 0.3030 | 10000 | 0.9639          | 0.0026                 | 0.4105 | 0.2169 |
| 0.4663        | 0.3333 | 11000 | 0.9689          | 0.0026                 | 0.4236 | 0.2245 |
| 0.3647        | 0.3636 | 12000 | 1.0025          | 0.0026                 | 0.4326 | 0.2297 |
| 0.451         | 0.3939 | 13000 | 0.8810          | 0.0026                 | 0.4648 | 0.2591 |
| 0.4522        | 0.4242 | 14000 | 0.8283          | 0.0026                 | 0.3869 | 0.1965 |
| 0.5064        | 0.4545 | 15000 | 0.8165          | 0.0026                 | 0.3703 | 0.1898 |
| 0.4355        | 0.4848 | 16000 | 0.7857          | 0.0026                 | 0.4367 | 0.2257 |
| 0.2953        | 0.5152 | 17000 | 0.8007          | 0.0026                 | 0.3650 | 0.2020 |
| 0.4345        | 0.5455 | 18000 | 0.7823          | 0.0026                 | 0.4544 | 0.2381 |
| 0.4117        | 0.5758 | 19000 | 0.7648          | 0.0026                 | 0.3595 | 0.1823 |
| 0.4071        | 0.6061 | 20000 | 0.7475          | 0.0026                 | 0.4121 | 0.2049 |
| 0.4371        | 0.6364 | 21000 | 0.7285          | 0.0026                 | 0.3509 | 0.1842 |
| 0.34          | 0.6667 | 22000 | 0.7686          | 0.0026                 | 0.3566 | 0.1860 |
| 0.335         | 0.6970 | 23000 | 0.7514          | 0.0026                 | 0.3595 | 0.1846 |
| 0.2946        | 0.7273 | 24000 | 0.7928          | 0.0026                 | 0.3742 | 0.2006 |
| 0.3916        | 0.7576 | 25000 | 0.6843          | 0.0026                 | 0.3416 | 0.1747 |
| 0.3233        | 0.7879 | 26000 | 0.6478          | 0.0026                 | 0.3178 | 0.1626 |
| 0.2981        | 0.8182 | 27000 | 0.6737          | 0.0026                 | 0.3274 | 0.1669 |
| 0.2945        | 0.8485 | 28000 | 0.6512          | 0.0026                 | 0.3302 | 0.1643 |
| 0.2956        | 0.8788 | 29000 | 0.6867          | 0.0026                 | 0.3925 | 0.1991 |
| 0.2541        | 0.9091 | 30000 | 0.6333          | 0.0026                 | 0.3186 | 0.1620 |
| 0.2475        | 0.9394 | 31000 | 0.7018          | 0.0026                 | 0.3343 | 0.1722 |
| 0.2951        | 0.9697 | 32000 | 0.6527          | 0.0026                 | 0.3168 | 0.1632 |
| 0.2879        | 1.0    | 33000 | 0.6440          | 0.0026                 | 0.3102 | 0.1560 |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.1