---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-base-thai-5-google-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-base-thai-5-google-colab

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5367
- Wer: 0.5438

## 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: 500
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 5.8705        | 0.88  | 400  | 3.6557          | 1.0    |
| 3.2446        | 1.77  | 800  | 1.8761          | 1.0173 |
| 1.6206        | 2.65  | 1200 | 0.9131          | 0.8479 |
| 1.2166        | 3.54  | 1600 | 0.7688          | 0.7733 |
| 1.0517        | 4.42  | 2000 | 0.6680          | 0.7191 |
| 0.9463        | 5.31  | 2400 | 0.6290          | 0.6903 |
| 0.8679        | 6.19  | 2800 | 0.5944          | 0.6736 |
| 0.8053        | 7.08  | 3200 | 0.5609          | 0.6405 |
| 0.7408        | 7.96  | 3600 | 0.5476          | 0.6294 |
| 0.6992        | 8.85  | 4000 | 0.5386          | 0.6046 |
| 0.6593        | 9.73  | 4400 | 0.5338          | 0.5962 |
| 0.6276        | 10.62 | 4800 | 0.5410          | 0.6087 |
| 0.5988        | 11.5  | 5200 | 0.5257          | 0.5850 |
| 0.5625        | 12.39 | 5600 | 0.4970          | 0.5780 |
| 0.5382        | 13.27 | 6000 | 0.5132          | 0.5638 |
| 0.5208        | 14.16 | 6400 | 0.5323          | 0.5696 |
| 0.5041        | 15.04 | 6800 | 0.5287          | 0.5644 |
| 0.4742        | 15.93 | 7200 | 0.5302          | 0.5744 |
| 0.4679        | 16.81 | 7600 | 0.5347          | 0.5501 |
| 0.453         | 17.7  | 8000 | 0.5413          | 0.5498 |
| 0.4424        | 18.58 | 8400 | 0.5418          | 0.5429 |
| 0.4283        | 19.47 | 8800 | 0.5367          | 0.5438 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1