---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-large-asr-th
  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-large-asr-th

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: 0.5920
- Wer: 0.5256
- Cer: 0.1778

## 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: 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: 200
- training_steps: 6000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 3.6977        | 0.57  | 500  | 3.6087          | 1.0    | 0.9999 |
| 3.4771        | 1.14  | 1000 | 3.4975          | 1.0    | 0.9999 |
| 2.6942        | 1.71  | 1500 | 2.2851          | 1.0067 | 0.6597 |
| 1.698         | 2.28  | 2000 | 1.0650          | 0.7875 | 0.3045 |
| 1.5008        | 2.85  | 2500 | 0.8698          | 0.6838 | 0.2508 |
| 1.1706        | 3.42  | 3000 | 0.7382          | 0.6132 | 0.2140 |
| 1.1872        | 4.0   | 3500 | 0.6924          | 0.5840 | 0.2029 |
| 1.1422        | 4.57  | 4000 | 0.6531          | 0.5690 | 0.1959 |
| 0.9556        | 5.14  | 4500 | 0.6246          | 0.5432 | 0.1850 |
| 1.0091        | 5.71  | 5000 | 0.6052          | 0.5360 | 0.1822 |
| 1.0523        | 6.28  | 5500 | 0.5995          | 0.5293 | 0.1802 |
| 1.0205        | 6.85  | 6000 | 0.5920          | 0.5256 | 0.1778 |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2