---
library_name: transformers
language:
- th
license: apache-2.0
base_model: openai/whisper-large
tags:
- asr
- speech-recognition
- thai
- custom-model
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Large TH - Nonhmello
  results: []
---

<!-- 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 Large TH - Nonhmello

This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the Custom dataset on local machine dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3642
- Wer: 50.0

## 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: 16
- eval_batch_size: 8
- 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: 800
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer  |
|:-------------:|:-----:|:----:|:---------------:|:----:|
| 0.0           | 400.0 | 400  | 0.3334          | 50.0 |
| 0.0           | 800.0 | 800  | 0.3642          | 50.0 |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3