---
license: cc-by-sa-4.0
tags:
- generated_from_trainer
datasets:
- common_voice
metrics:
- wer
model-index:
- name: wav2vec2-large-xlsr-53-thai
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice
      type: common_voice
      config: th
      split: validation
      args: th
    metrics:
    - name: Wer
      type: wer
      value: 0.7430683918669131
---

<!-- 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-xlsr-53-thai

This model is a fine-tuned version of [airesearch/wav2vec2-large-xlsr-53-th](https://huggingface.co/airesearch/wav2vec2-large-xlsr-53-th) on the common_voice dataset.
It achieves the following results on the evaluation set:
- Loss: 3.3576
- Wer: 0.7431

## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 6.7312        | 3.33  | 100  | 3.3592          | 1.0    |
| 3.3687        | 6.67  | 200  | 3.2175          | 1.0    |
| 2.4527        | 10.0  | 300  | 2.2648          | 0.7911 |
| 1.0505        | 13.33 | 400  | 2.2322          | 0.7659 |
| 0.7725        | 16.67 | 500  | 2.2775          | 0.7505 |
| 0.6289        | 20.0  | 600  | 2.3209          | 0.7498 |
| 0.543         | 23.33 | 700  | 2.4494          | 0.7572 |
| 0.4991        | 26.67 | 800  | 2.5798          | 0.7597 |
| 0.4492        | 30.0  | 900  | 2.5685          | 0.7461 |
| 0.3737        | 33.33 | 1000 | 2.6186          | 0.7486 |
| 0.3358        | 36.67 | 1100 | 2.7781          | 0.7480 |
| 0.3247        | 40.0  | 1200 | 2.8999          | 0.7535 |
| 0.2963        | 43.33 | 1300 | 2.8668          | 0.7388 |
| 0.2825        | 46.67 | 1400 | 2.8983          | 0.7449 |
| 0.2651        | 50.0  | 1500 | 2.9699          | 0.7461 |
| 0.2597        | 53.33 | 1600 | 2.9930          | 0.7314 |
| 0.2629        | 56.67 | 1700 | 2.9852          | 0.7406 |
| 0.2406        | 60.0  | 1800 | 3.0552          | 0.7474 |
| 0.2293        | 63.33 | 1900 | 3.1058          | 0.7344 |
| 0.2193        | 66.67 | 2000 | 3.1594          | 0.7406 |
| 0.2174        | 70.0  | 2100 | 3.2351          | 0.7369 |
| 0.2127        | 73.33 | 2200 | 3.2696          | 0.7388 |
| 0.2061        | 76.67 | 2300 | 3.2954          | 0.7566 |
| 0.1947        | 80.0  | 2400 | 3.2878          | 0.7529 |
| 0.199         | 83.33 | 2500 | 3.3233          | 0.7486 |
| 0.1961        | 86.67 | 2600 | 3.3136          | 0.7437 |
| 0.1928        | 90.0  | 2700 | 3.3240          | 0.7406 |
| 0.1875        | 93.33 | 2800 | 3.3479          | 0.7425 |
| 0.1852        | 96.67 | 2900 | 3.3681          | 0.7425 |
| 0.1814        | 100.0 | 3000 | 3.3576          | 0.7431 |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 1.16.1
- Tokenizers 0.13.3