---
language:
- th
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
- lotus
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Small Thai 7k
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_11_0 th
      type: mozilla-foundation/common_voice_11_0
      config: th
      split: test
      args: th
    metrics:
    - name: Wer
      type: wer
      value: 14.69
---

<!-- 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 Tiny Thai

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0, lotus, google/fleurs th,None,th_th dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2262
- Wer: 14.69

## 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: 1e-05
- train_batch_size: 64
- 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: 7000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0473        | 0.14  | 1000 | 0.2459          | 21.6283 |
| 0.0253        | 1.07  | 2000 | 0.1970          | 17.2157 |
| 0.0181        | 2.0   | 3000 | 0.2017          | 17.8993 |
| 0.0088        | 2.15  | 4000 | 0.2148          | 16.8428 |
| 0.0055        | 3.07  | 5000 | 0.2166          | 15.8484 |
| 0.0048        | 4.0   | 6000 | 0.2261          | 16.0348 |
| 0.0026        | 4.15  | 7000 | 0.2262          | 15.5998 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2