---
language:
- th
license: apache-2.0
base_model: openai/whisper-base
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_0
metrics:
- wer
model-index:
- name: Whisper Base Thai
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_16_0 th
      type: mozilla-foundation/common_voice_16_0
      config: th
      split: test
      args: th
    metrics:
    - name: Wer
      type: wer
      value: 44.56011784657663
---

<!-- 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 Base Thai

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the mozilla-foundation/common_voice_16_0 th dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4390
- Wer: 44.5601

## 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-07
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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 | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.8395        | 1.02  | 500   | 0.7280          | 60.6811 |
| 0.7819        | 2.03  | 1000  | 0.6414          | 56.1244 |
| 0.6456        | 4.01  | 1500  | 0.5940          | 53.4778 |
| 0.6091        | 5.03  | 2000  | 0.5633          | 52.0691 |
| 0.5465        | 7.01  | 2500  | 0.5383          | 50.4822 |
| 0.5406        | 8.02  | 3000  | 0.5200          | 49.5537 |
| 0.4863        | 10.01 | 3500  | 0.5047          | 48.9992 |
| 0.4691        | 11.02 | 4000  | 0.4919          | 47.9767 |
| 0.5183        | 13.0  | 4500  | 0.4823          | 47.6833 |
| 0.5025        | 14.02 | 5000  | 0.4730          | 46.7202 |
| 0.5426        | 15.03 | 5500  | 0.4661          | 46.3501 |
| 0.4713        | 17.01 | 6000  | 0.4594          | 45.9985 |
| 0.4274        | 18.03 | 6500  | 0.4546          | 45.6061 |
| 0.4248        | 20.01 | 7000  | 0.4500          | 45.3598 |
| 0.4404        | 21.03 | 7500  | 0.4467          | 45.1097 |
| 0.4144        | 23.01 | 8000  | 0.4438          | 44.8411 |
| 0.4004        | 24.02 | 8500  | 0.4416          | 44.6938 |
| 0.4165        | 26.0  | 9000  | 0.4403          | 44.6443 |
| 0.4218        | 27.02 | 9500  | 0.4393          | 44.5750 |
| 0.453         | 28.03 | 10000 | 0.4390          | 44.5601 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0