---
language:
- br
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: openai/whisper-large-v2-breton
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: br
      split: test
      args: br
    metrics:
    - name: Wer
      type: wer
      value: 39.92705800625217
---

<!-- 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. -->

# openai/whisper-large-v2-breton

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7162
- Wer: 39.9271

## 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: 16
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 1000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.7423        | 0.1   | 100  | 0.8363          | 57.1553 |
| 0.4361        | 1.07  | 200  | 0.6833          | 46.7176 |
| 0.2227        | 2.03  | 300  | 0.6483          | 42.5929 |
| 0.1472        | 3.0   | 400  | 0.6511          | 42.4627 |
| 0.0892        | 3.1   | 500  | 0.6633          | 40.9604 |
| 0.0651        | 4.07  | 600  | 0.6807          | 39.7534 |
| 0.0416        | 5.04  | 700  | 0.6870          | 41.2383 |
| 0.0352        | 6.0   | 800  | 0.7315          | 39.9010 |
| 0.022         | 6.1   | 900  | 0.7201          | 40.4307 |
| 0.0195        | 7.07  | 1000 | 0.7162          | 39.9271 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2