pytorch tensorboard wav2vec2 automatic-speech-recognition gn dataset:common_voice transformers generated_from_trainer robust-speech-event hf-asr-leaderboard license:apache-2.0 model-index
---
language:
- gn
license: apache-2.0
tags:
- generated_from_trainer
- robust-speech-event
- gn
- hf-asr-leaderboard
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-guarani-small
  results: []
---

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# wav2vec2-large-xls-r-300m-guarani-small

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 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4964
- Wer: 0.5957

## 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: 0.0002
- 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: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 6.65  | 100  | 1.1326          | 1.0    |
| 1.6569        | 13.32 | 200  | 0.5264          | 0.6478 |
| 1.6569        | 19.97 | 300  | 0.5370          | 0.6261 |
| 0.2293        | 26.65 | 400  | 0.4964          | 0.5957 |


### Framework versions

- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.0
