whisper-burmese-myanify

tettoewai/whisper-burmese-myanify

whisper-burmese-myanify is a automatic speech recognition model from tettoewai. Use it when you need speech turned into text. It is set up for transformers.

should probably proofread and complete it, then remove this comment. --

Downloads · 30 days

3% of all-time downloads

All-time downloads

510

Public

Parameters

242M

32.9 GB on disk

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors967 MB · 100%

At a glance

Task: Automatic Speech Recognition
Library: transformers
Model type: whisper
Access: Public
Created: Jun 14, 2026
Updated: Sep 14, 2026
SHA: e5a2235c

Model card

From the Hugging Face model README

whisper-burmese-myanify

This model is a fine-tuned version of tettoewai/whisper-burmese-myanify on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.4011
Cer: 0.5333

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
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 200
training_steps: 1500
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Cer
0.0048	1.4286	250	0.3871	0.5407
0.0040	2.8571	500	0.3830	0.5418
0.0014	4.2857	750	0.3918	0.5389
0.0005	5.7143	1000	0.3983	0.5357
0.0001	7.1429	1250	0.3970	0.5344
0.0001	8.5714	1500	0.4011	0.5333

Framework versions

Transformers 5.0.0
Pytorch 2.10.0+cu128
Datasets 5.0.0
Tokenizers 0.22.2

Task: Automatic Speech Recognition
Library: transformers
Type: whisper
Created: Jun 14, 2026
Updated: Sep 14, 2026