---
library_name: peft
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: 37.2840522511834
      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: 0.1197
- Cer: 347.2750
- Wer: 37.2841

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use paged_adamw_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Cer      | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:-------:|
| 0.1468        | 1.0   | 2052  | 0.1265          | 348.7140 | 42.3821 |
| 0.1225        | 2.0   | 4104  | 0.1178          | 387.4029 | 34.6267 |
| 0.0914        | 3.0   | 6156  | 0.1157          | 368.2561 | 36.4184 |
| 0.0779        | 4.0   | 8208  | 0.1182          | 347.7405 | 36.8434 |
| 0.0624        | 5.0   | 10260 | 0.1197          | 347.2750 | 37.2841 |


### Framework versions

- PEFT 0.14.1.dev0
- Transformers 4.49.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0