---
base_model: openai/whisper-small
datasets:
- fruk19/N_asr
language:
- th
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: North_asri
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: aicookcook
      type: fruk19/N_asr
      config: default
      split: None
      args: 'config: th'
    metrics:
    - type: wer
      value: 5.772624833690841
      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. -->

# North_asri

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: 0.0764
- Wer: 5.7726

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.0486        | 2.0   | 6000  | 0.0722          | 9.8591 |
| 0.0125        | 4.0   | 12000 | 0.0682          | 6.9130 |
| 0.0038        | 6.0   | 18000 | 0.0722          | 6.3537 |
| 0.0019        | 8.0   | 24000 | 0.0752          | 5.9627 |
| 0.0001        | 10.0  | 30000 | 0.0764          | 5.7726 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.0.1+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1