---
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: 0.6198
- Wer: 0.5833

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 5.8342        | 1.28  | 400  | 3.5303          | 1.0    |
| 3.0206        | 2.56  | 800  | 1.3367          | 0.9586 |
| 1.4665        | 3.84  | 1200 | 0.8291          | 0.8033 |
| 1.1346        | 5.12  | 1600 | 0.7229          | 0.7274 |
| 0.9699        | 6.4   | 2000 | 0.6384          | 0.7101 |
| 0.8754        | 7.68  | 2400 | 0.6393          | 0.6990 |
| 0.8001        | 8.96  | 2800 | 0.6427          | 0.6626 |
| 0.7116        | 10.24 | 3200 | 0.5992          | 0.6534 |
| 0.6743        | 11.52 | 3600 | 0.5936          | 0.6310 |
| 0.632         | 12.8  | 4000 | 0.6278          | 0.6348 |
| 0.5862        | 14.08 | 4400 | 0.6026          | 0.6152 |
| 0.563         | 15.36 | 4800 | 0.6020          | 0.5931 |
| 0.5359        | 16.64 | 5200 | 0.6278          | 0.5954 |
| 0.5065        | 17.92 | 5600 | 0.6273          | 0.5999 |
| 0.4958        | 19.2  | 6000 | 0.6198          | 0.5833 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0