đ Whisper Medium (Thai): Combined V3
This model is a fine - tuned version of [openai/whisper - medium](https://huggingface.co/openai/whisper - medium) for Thai automatic speech recognition, achieving high performance on relevant datasets.
đ Quick Start
This model is a fine - tuned version of [openai/whisper - medium](https://huggingface.co/openai/whisper - medium) on augmented versions of the mozilla - foundation/common_voice_13_0 th, google/fleurs, and curated datasets.
It achieves the following results on the common - voice - 13 test set:
- WER: 7.42 (with Deepcut Tokenizer)
đģ Usage Examples
Basic Usage
from transformers import pipeline
MODEL_NAME = "biodatlab/whisper - th - medium - combined"
lang = "th"
device = 0 if torch.cuda.is_available() else "cpu"
pipe = pipeline(
task="automatic - speech - recognition",
model=MODEL_NAME,
chunk_length_s=30,
device=device,
)
pipe.model.config.forced_decoder_ids = pipe.tokenizer.get_decoder_prompt_ids(
language=lang,
task="transcribe"
)
text = pipe("audio.mp3")["text"]
đ Documentation
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: AdamW with betas=(0.9,0.999) and epsilon=1e - 08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0
- Datasets 2.16.1
- Tokenizers 0.15.1
đ License
This model is licensed under the Apache - 2.0 license.
đ Citation
Cite using Bibtex:
@misc {thonburian_whisper_med,
author = { Atirut Boribalburephan, Zaw Htet Aung, Knot Pipatsrisawat, Titipat Achakulvisut },
title = { Thonburian Whisper: A fine - tuned Whisper model for Thai automatic speech recognition },
year = 2022,
url = { https://huggingface.co/biodatlab/whisper - th - medium - combined },
doi = { 10.57967/hf/0226 },
publisher = { Hugging Face }
}