---
license: apache-2.0
base_model: arun100/whisper-base-th-1
tags:
- whisper-event
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Base Thai (2)
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: google/fleurs th_th
      type: google/fleurs
      config: th_th
      split: test
      args: th_th
    metrics:
    - name: Wer
      type: wer
      value: 53.662828506943114
---

<!-- 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 (2)

This model is a fine-tuned version of [arun100/whisper-base-th-1](https://huggingface.co/arun100/whisper-base-th-1) on the google/fleurs th_th dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5628
- Wer: 53.6628

## 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: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.5011        | 35.0  | 500  | 0.5963          | 59.8868 |
| 0.3648        | 71.0  | 1000 | 0.5613          | 55.9542 |
| 0.2732        | 107.0 | 1500 | 0.5504          | 54.4585 |
| 0.2081        | 142.0 | 2000 | 0.5502          | 53.6705 |
| 0.1627        | 178.0 | 2500 | 0.5558          | 53.8273 |
| 0.133         | 214.0 | 3000 | 0.5628          | 53.6628 |
| 0.1112        | 249.0 | 3500 | 0.5696          | 54.0798 |
| 0.0973        | 285.0 | 4000 | 0.5749          | 53.9995 |
| 0.0906        | 321.0 | 4500 | 0.5783          | 54.1487 |
| 0.0874        | 357.0 | 5000 | 0.5793          | 54.2290 |


### Framework versions

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