pytorch wav2vec2 automatic-speech-recognition dataset:common_voice transformers generated_from_trainer license:apache-2.0 model-index
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-tr-colab
  results: []
---

<!-- 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-tr-colab

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: 0.4121
- Wer: 0.3112

## 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
- distributed_type: multi-GPU
- 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 4.1868        | 1.83  | 400  | 0.9812          | 0.8398 |
| 0.691         | 3.67  | 800  | 0.5571          | 0.6298 |
| 0.3555        | 5.5   | 1200 | 0.4676          | 0.4779 |
| 0.2451        | 7.34  | 1600 | 0.4572          | 0.4541 |
| 0.1844        | 9.17  | 2000 | 0.4743          | 0.4389 |
| 0.1541        | 11.01 | 2400 | 0.4583          | 0.4300 |
| 0.1277        | 12.84 | 2800 | 0.4565          | 0.3950 |
| 0.1122        | 14.68 | 3200 | 0.4761          | 0.4087 |
| 0.0975        | 16.51 | 3600 | 0.4654          | 0.3786 |
| 0.0861        | 18.35 | 4000 | 0.4503          | 0.3667 |
| 0.0775        | 20.18 | 4400 | 0.4600          | 0.3581 |
| 0.0666        | 22.02 | 4800 | 0.4350          | 0.3504 |
| 0.0627        | 23.85 | 5200 | 0.4211          | 0.3349 |
| 0.0558        | 25.69 | 5600 | 0.4390          | 0.3333 |
| 0.0459        | 27.52 | 6000 | 0.4218          | 0.3185 |
| 0.0439        | 29.36 | 6400 | 0.4121          | 0.3112 |


### Framework versions

- Transformers 4.11.3
- Pytorch 1.10.2+cu102
- Datasets 1.18.3
- Tokenizers 0.10.3
