---
language:
- th
license: apache-2.0
tags:
- generated_from_trainer
base_model: openai/whisper-small
datasets:
- aicookcook
metrics:
- wer
model-index:
- name: all_asr
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: aicookcook
      type: aicookcook
      args: config:th
    metrics:
    - type: wer
      value: 18.262970669172425
      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. -->

# all_asr

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the aicookcook dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1879
- Wer: 18.2630

## 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: 5
- eval_batch_size: 5
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.0586        | 3.0048 | 2500 | 0.1755          | 19.9779 |
| 0.0038        | 6.0096 | 5000 | 0.1879          | 18.2630 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1