---
tags:
- generated_from_trainer
metrics:
- wer
- cer
model-index:
- name: wav2vec2-large-asr-th-2
  results: []
datasets:
- common_voice
- mozilla-foundation/common_voice_10_0
language:
- th
pipeline_tag: automatic-speech-recognition
library_name: transformers
---

<!-- 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-asr-th-2

This model was find-tune from  on the CommonVoice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2310
- Wer: 32.99%
- Cer: 3.75%

## 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: 1e-05
- train_batch_size: 12
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 3
- total_train_batch_size: 36
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 0.065         | 0.18  | 1000 | 0.5433          | 0.3259 | 0.0891 |
| 0.0792        | 0.36  | 2000 | 0.5453          | 0.3269 | 0.0901 |
| 0.1663        | 0.53  | 3000 | 0.4702          | 0.3299 | 0.0908 |
| 0.7971        | 0.71  | 4000 | 0.2513          | 0.3244 | 0.0889 |
| 0.7588        | 0.89  | 5000 | 0.2310          | 0.3196 | 0.0878 |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3