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---
license: cc-by-nc-nd-4.0
datasets:
- openslr
language:
- gl
pipeline_tag: automatic-speech-recognition
tags:
- ITG
- PyTorch
- Transformers
- wav2vec2
---
# Wav2Vec2 Large XLSR Galician
## Description
This is a fine-tuned version of the [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) pre-trained model for ASR in galician.
---
## Dataset
The dataset used for fine-tuning this model was the [OpenSLR galician](https://huggingface.co/datasets/openslr/viewer/SLR77) dataset, available in the openslr repository.
---
## Example inference script
### Check this example script to run our model in inference mode
```python
import torch
from transformers import AutoProcessor, AutoModelForCTC
filename = "demo.wav" #change this line to the name of your audio file
sample_rate = 16_000
processor = AutoProcessor.from_pretrained('ITG/wav2vec2-large-xlsr-gl')
model = AutoModelForSpeechSeq2Seq.from_pretrained('ITG/wav2vec2-large-xlsr-gl')
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
model.to(device)
speech_array, _ = librosa.load(filename, sr=sample_rate)
inputs = processor(speech_array, sampling_rate=sample_rate, return_tensors="pt", padding=True).to(device)
with torch.no_grad():
logits = model(inputs.input_values, attention_mask=inputs.attention_mask.to(device)).logits
decode_output = processor.batch_decode(torch.argmax(logits, dim=-1))[0]
print(f"ASR Galician wav2vec2-large-xlsr output: {decode_output}")
```
---
## Fine-tuning hyper-parameters
| **Hyper-parameter** | **Value** |
|:----------------------------------------:|:---------------------------:|
| Training batch size | 16 |
| Evaluation batch size | 8 |
| Learning rate | 3e-4 |
| Gradient accumulation steps | 2 |
| Group by length | true |
| Evaluation strategy | steps |
| Max training epochs | 50 |
| Max steps | 4000 |
| Generate max length | 225 |
| FP16 | true |
| Metric for best model | wer |
| Greater is better | false |
## Fine-tuning in a different dataset or style
If you're interested in fine-tuning your own wav2vec2 model, we suggest starting with the [facebook/wav2vec2-large-xlsr-53 model](https://huggingface.co/facebook/wav2vec2-large-xlsr-53). Additionally,
you may find this [fine-tuning on galician notebook by Diego Fustes](https://github.com/diego-fustes/xlsr-fine-tuning-gl/blob/main/Fine_Tune_XLSR_Wav2Vec2_on_Galician.ipynb) to be a valuable resource.
This guide served as a helpful reference during the training process of this Galician wav2vec2-large-xlsr model!
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