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---
library_name: transformers
language:
- th
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper Large v3 Thai Finetuned
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Common Voice 17.0
type: mozilla-foundation/common_voice_17_0
config: th
split: None
args: 'config: th, split: train'
metrics:
- type: wer
value: 37.14119683781068
name: Wer
---
<!-- 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. -->
# Whisper Large v3 Thai Finetuned
This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the Common Voice 17.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2345
- Cer: 10.6496
- Wer: 37.1412
## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Cer | Wer |
|:-------------:|:------:|:-----:|:---------------:|:--------:|:-------:|
| 0.2027 | 0.4873 | 500 | 0.1805 | 107.2858 | 75.0935 |
| 0.1674 | 0.9747 | 1000 | 0.1508 | 8.7078 | 41.0794 |
| 0.1073 | 1.4620 | 1500 | 0.1506 | 38.7265 | 45.4534 |
| 0.1035 | 1.9493 | 2000 | 0.1372 | 10.7331 | 38.5129 |
| 0.0587 | 2.4366 | 2500 | 0.1438 | 16.8383 | 50.0563 |
| 0.0627 | 2.9240 | 3000 | 0.1397 | 10.6251 | 31.3447 |
| 0.0356 | 3.4113 | 3500 | 0.1497 | 7.8515 | 33.7998 |
| 0.0367 | 3.8986 | 4000 | 0.1456 | 18.7090 | 37.0359 |
| 0.0184 | 4.3860 | 4500 | 0.1606 | 39.3584 | 93.1345 |
| 0.0204 | 4.8733 | 5000 | 0.1596 | 8.4796 | 31.7272 |
| 0.0112 | 5.3606 | 5500 | 0.1730 | 4.8027 | 25.0106 |
| 0.0119 | 5.8480 | 6000 | 0.1697 | 36.5628 | 82.3949 |
| 0.0057 | 6.3353 | 6500 | 0.1800 | 17.5990 | 50.1931 |
| 0.0052 | 6.8226 | 7000 | 0.1789 | 48.1183 | 98.1247 |
| 0.003 | 7.3099 | 7500 | 0.1960 | 15.7676 | 41.7634 |
| 0.0028 | 7.7973 | 8000 | 0.1980 | 15.2090 | 54.8407 |
| 0.001 | 8.2846 | 8500 | 0.2091 | 21.4387 | 68.7365 |
| 0.001 | 8.7719 | 9000 | 0.2175 | 11.7533 | 40.0988 |
| 0.0001 | 9.2593 | 9500 | 0.2327 | 13.1280 | 40.6133 |
| 0.0001 | 9.7466 | 10000 | 0.2345 | 10.6496 | 37.1412 |
### Framework versions
- Transformers 4.45.2
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1
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