---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: ASR_dear_wav2vec2-thai
  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. -->

# ASR_dear_wav2vec2-thai

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: 0.3333
- Wer: 0.3905

## 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: 1000
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 7.8205        | 0.75  | 1000  | 3.5802          | 1.0    |
| 1.9581        | 1.5   | 2000  | 0.6882          | 0.7315 |
| 0.9012        | 2.24  | 3000  | 0.5229          | 0.6245 |
| 0.7558        | 2.99  | 4000  | 0.4531          | 0.5812 |
| 0.6671        | 3.74  | 5000  | 0.4277          | 0.5305 |
| 0.6083        | 4.49  | 6000  | 0.4067          | 0.5234 |
| 0.5633        | 5.24  | 7000  | 0.3821          | 0.4831 |
| 0.5335        | 5.98  | 8000  | 0.3682          | 0.4928 |
| 0.5021        | 6.73  | 9000  | 0.3578          | 0.4568 |
| 0.4806        | 7.48  | 10000 | 0.3508          | 0.4609 |
| 0.4554        | 8.23  | 11000 | 0.3518          | 0.4458 |
| 0.4361        | 8.98  | 12000 | 0.3375          | 0.4430 |
| 0.411         | 9.72  | 13000 | 0.3363          | 0.4269 |
| 0.3998        | 10.47 | 14000 | 0.3382          | 0.4221 |
| 0.3851        | 11.22 | 15000 | 0.3351          | 0.4161 |
| 0.3713        | 11.97 | 16000 | 0.3353          | 0.4106 |
| 0.3539        | 12.72 | 17000 | 0.3287          | 0.4084 |
| 0.3468        | 13.46 | 18000 | 0.3282          | 0.4098 |
| 0.3369        | 14.21 | 19000 | 0.3278          | 0.4015 |
| 0.3276        | 14.96 | 20000 | 0.3285          | 0.3968 |
| 0.3207        | 15.71 | 21000 | 0.3322          | 0.3980 |
| 0.31          | 16.45 | 22000 | 0.3379          | 0.3948 |
| 0.3043        | 17.2  | 23000 | 0.3264          | 0.3938 |
| 0.2975        | 17.95 | 24000 | 0.3299          | 0.3933 |
| 0.2959        | 18.7  | 25000 | 0.3299          | 0.3918 |
| 0.2898        | 19.45 | 26000 | 0.3333          | 0.3905 |


### Framework versions

- Transformers 4.27.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2