transformers tensorboard safetensors wav2vec2 automatic-speech-recognition generated_from_trainer dataset:common_voice_13_0 base_model:facebook/wav2vec2-large-xlsr-53-spanish license:apache-2.0 model-index endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53-spanish
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-gn
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_13_0
      type: common_voice_13_0
      config: gn
      split: test
      args: gn
    metrics:
    - name: Wer
      type: wer
      value: 0.3430613460393091
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# wav2vec2-large-xls-r-300m-gn

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53-spanish](https://huggingface.co/facebook/wav2vec2-large-xlsr-53-spanish) on the common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3713
- Wer: 0.3431

## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.7177        | 3.62  | 400  | 0.3649          | 0.5816 |
| 0.2738        | 7.24  | 800  | 0.4029          | 0.5024 |
| 0.1768        | 10.86 | 1200 | 0.3779          | 0.4285 |
| 0.1128        | 14.48 | 1600 | 0.3929          | 0.4205 |
| 0.0842        | 18.1  | 2000 | 0.3683          | 0.3916 |
| 0.0616        | 21.72 | 2400 | 0.3943          | 0.3675 |
| 0.0461        | 25.34 | 2800 | 0.4127          | 0.3571 |
| 0.0368        | 28.96 | 3200 | 0.3713          | 0.3431 |


### Framework versions

- Transformers 4.35.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
