---
library_name: transformers
license: mit
base_model: openai/whisper-large-v3-turbo
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-medium-CAENNAIS
  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-medium-CAENNAIS

This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5740
- Wer: 26.7396

## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 16
- 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
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| No log        | 1.0   | 56   | 0.7664          | 33.4990 |
| No log        | 2.0   | 112  | 0.4936          | 28.0649 |
| No log        | 3.0   | 168  | 0.4702          | 23.7906 |
| No log        | 4.0   | 224  | 0.4987          | 28.4957 |
| No log        | 5.0   | 280  | 0.4999          | 23.7575 |
| No log        | 6.0   | 336  | 0.5567          | 25.3810 |
| No log        | 7.0   | 392  | 0.5685          | 23.4924 |
| No log        | 8.0   | 448  | 0.5738          | 25.0497 |
| 0.3662        | 9.0   | 504  | 0.6081          | 24.6852 |
| 0.3662        | 10.0  | 560  | 0.5740          | 26.7396 |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.0