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---
language:
- br
license: apache-2.0
tags:
- generated_from_trainer
base_model: facebook/wav2vec2-xls-r-300m
datasets:
- mozilla-foundation/common_voice_15_0
metrics:
- wer
model-index:
- name: wav2vec2-xls-r-300m-breton
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. -->
# wav2vec2-xls-r-300m-breton
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co./facebook/wav2vec2-xls-r-300m) on the [mozilla-foundation/common_voice_15_0]() dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9939
- Wer: 0.4680
- Cer: 0.1711
## 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: 6e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- 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_ratio: 0.08
- num_epochs: 50
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 10.4347 | 2.56 | 250 | 3.7906 | 1.0 | 1.0 |
| 3.2144 | 5.13 | 500 | 3.0622 | 1.0 | 1.0 |
| 2.6193 | 7.69 | 750 | 1.6063 | 0.9122 | 0.4042 |
| 1.3658 | 10.26 | 1000 | 1.0917 | 0.7061 | 0.2474 |
| 0.9614 | 12.82 | 1250 | 0.9805 | 0.6384 | 0.2245 |
| 0.7915 | 15.38 | 1500 | 0.9340 | 0.5989 | 0.2124 |
| 0.6728 | 17.95 | 1750 | 0.9135 | 0.5735 | 0.2016 |
| 0.5889 | 20.51 | 2000 | 0.9381 | 0.5443 | 0.1944 |
| 0.5374 | 23.08 | 2250 | 0.9517 | 0.5372 | 0.1918 |
| 0.4972 | 25.64 | 2500 | 0.9171 | 0.5134 | 0.1828 |
| 0.4537 | 28.21 | 2750 | 0.9457 | 0.5043 | 0.1804 |
| 0.4217 | 30.77 | 3000 | 0.9479 | 0.4957 | 0.1789 |
| 0.4082 | 33.33 | 3250 | 0.9400 | 0.4906 | 0.1762 |
| 0.4005 | 35.9 | 3500 | 0.9710 | 0.4881 | 0.1770 |
| 0.3702 | 38.46 | 3750 | 0.9922 | 0.4792 | 0.1757 |
| 0.3473 | 41.03 | 4000 | 0.9724 | 0.4760 | 0.1734 |
| 0.3405 | 43.59 | 4250 | 0.9860 | 0.4726 | 0.1722 |
| 0.325 | 46.15 | 4500 | 0.9888 | 0.4679 | 0.1705 |
| 0.3193 | 48.72 | 4750 | 0.9939 | 0.4680 | 0.1711 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0 |