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---
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
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