---
license: cc-by-sa-4.0
tags:
- generated_from_trainer
datasets:
- common_voice
metrics:
- wer
model-index:
- name: wav2vec2-large-xlsr-53-th-main
  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: 0.4686162624821683
---

<!-- 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-th-main

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: 1.1340
- Wer: 0.4686

## 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: 30
- num_epochs: 40
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 5.2524        | 3.23  | 100  | 3.3222          | 1.0    |
| 3.2913        | 6.45  | 200  | 3.1818          | 1.0    |
| 2.222         | 9.68  | 300  | 1.2497          | 0.5335 |
| 1.1558        | 12.9  | 400  | 1.0792          | 0.5214 |
| 0.934         | 16.13 | 500  | 1.0663          | 0.4986 |
| 0.8023        | 19.35 | 600  | 1.0331          | 0.4893 |
| 0.7041        | 22.58 | 700  | 1.0801          | 0.4800 |
| 0.6576        | 25.81 | 800  | 1.1123          | 0.4886 |
| 0.6061        | 29.03 | 900  | 1.0748          | 0.4829 |
| 0.5649        | 32.26 | 1000 | 1.1187          | 0.4679 |
| 0.5717        | 35.48 | 1100 | 1.1267          | 0.4715 |
| 0.5267        | 38.71 | 1200 | 1.1340          | 0.4686 |


### Framework versions

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