---
language:
- gl
license: apache-2.0
tags:
- automatic-speech-recognition
- generated_from_trainer
- gl
- hf-asr-leaderboard
- model_for_talk
- mozilla-foundation/common_voice_7_0
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_7_0
model-index:
- name: XLS-R-300M - Galician
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 7.0
type: mozilla-foundation/common_voice_7_0
args: gl
metrics:
- name: Test WER
type: wer
value: 101.54
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Robust Speech Event - Dev Data
type: speech-recognition-community-v2/dev_data
args: gl
metrics:
- name: Test WER
type: wer
value: 105.69
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Robust Speech Event - Test Data
type: speech-recognition-community-v2/eval_data
args: gl
metrics:
- name: Test WER
type: wer
value: 101.95
---
<!-- 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-galician
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 - GL dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1525
- Wer: 0.1542
## 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: 20.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.0067 | 4.35 | 500 | 2.9632 | 1.0 |
| 1.4939 | 8.7 | 1000 | 0.5005 | 0.4157 |
| 0.9982 | 13.04 | 1500 | 0.1967 | 0.1857 |
| 0.8726 | 17.39 | 2000 | 0.1587 | 0.1564 |
### Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.17.1.dev0
- Tokenizers 0.11.0