---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-gn-pt
  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: 0.5964860035735556
---

<!-- 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-gn-pt

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6576
- Wer: 0.5965

## 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: 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_steps: 100
- num_epochs: 35

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 4.7255        | 4.85  | 400  | 3.0288          | 1.0    |
| 1.1814        | 9.7   | 800  | 0.5687          | 0.7317 |
| 0.3099        | 14.55 | 1200 | 0.6297          | 0.6828 |
| 0.1719        | 19.39 | 1600 | 0.7157          | 0.6992 |
| 0.1185        | 24.24 | 2000 | 0.6896          | 0.6537 |
| 0.0871        | 29.09 | 2400 | 0.7071          | 0.6215 |
| 0.0647        | 33.94 | 2800 | 0.6576          | 0.5965 |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1