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---
language:
- br
license: apache-2.0
tags:
- automatic-speech-recognition
- generated_from_trainer
- hf-asr-leaderboard
- mozilla-foundation/common_voice_7_0
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_7_0
model-index:
- name: XLS-R-300M - Breton
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 7
type: mozilla-foundation/common_voice_7_0
args: br
metrics:
- name: Test WER
type: wer
value: 107.955
- name: Test CER
type: cer
value: 379.33
---
<!-- 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-large-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_7_0 - BR dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6102
- Wer: 0.4455
## 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: 7e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 50.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.9205 | 3.33 | 500 | 2.8659 | 1.0 |
| 1.6403 | 6.67 | 1000 | 0.9440 | 0.7593 |
| 1.3483 | 10.0 | 1500 | 0.7580 | 0.6215 |
| 1.2255 | 13.33 | 2000 | 0.6851 | 0.5722 |
| 1.1139 | 16.67 | 2500 | 0.6409 | 0.5220 |
| 1.0688 | 20.0 | 3000 | 0.6245 | 0.5055 |
| 0.99 | 23.33 | 3500 | 0.6142 | 0.4874 |
| 0.9345 | 26.67 | 4000 | 0.5946 | 0.4829 |
| 0.9058 | 30.0 | 4500 | 0.6229 | 0.4704 |
| 0.8683 | 33.33 | 5000 | 0.6153 | 0.4666 |
| 0.8367 | 36.67 | 5500 | 0.5952 | 0.4542 |
| 0.8162 | 40.0 | 6000 | 0.6030 | 0.4541 |
| 0.8042 | 43.33 | 6500 | 0.5972 | 0.4485 |
| 0.7836 | 46.67 | 7000 | 0.6070 | 0.4497 |
| 0.7556 | 50.0 | 7500 | 0.6102 | 0.4455 |
### Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.17.1.dev0
- Tokenizers 0.11.0
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