---
library_name: transformers
language:
- th
license: apache-2.0
base_model: openai/whisper-medium
tags:
- asr
- speech-recognition
- thai
- custom-model
- fine-tuning
- Common Voice
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Medium TH - Custom datasets and Common voice 17
  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 Medium TH - Custom datasets and Common voice 17

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1365
- Wer: 59.1432

## 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: 16
- 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: 3000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.267         | 0.2405 | 500  | 0.2401          | 77.2512 |
| 0.1975        | 0.4810 | 1000 | 0.1865          | 68.8672 |
| 0.1935        | 0.7215 | 1500 | 0.1659          | 64.4477 |
| 0.1591        | 0.9620 | 2000 | 0.1477          | 63.3167 |
| 0.0821        | 1.2025 | 2500 | 0.1431          | 60.2557 |
| 0.0762        | 1.4430 | 3000 | 0.1365          | 59.1432 |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3