whisper-muong-final

longgb/whisper-muong-final

whisper-muong-final is a machine learning model from longgb. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as apache-2.0.

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

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Hugging Face

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At a glance

Library: peft
License: apache-2.0
Access: Public
Created: Dec 11, 2025
Updated: Dec 12, 2025
SHA: ee22b6f0

Base models

openai/whisper-large-v3

Model card

From the Hugging Face model README

whisper-muong-final

This model is a fine-tuned version of openai/whisper-large-v3 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.8115
Wer: 74.2356

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: 0.001
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 32
optimizer: Use OptimizerNames.ADAMW_TORCH 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: 50
training_steps: 800
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.7784	1.6393	200	0.8489	63.1697
0.4274	3.2787	400	0.7574	77.2651
0.3129	4.9180	600	0.7454	76.8724
0.1506	6.5574	800	0.8115	74.2356

Framework versions

PEFT 0.18.0
Transformers 4.57.3
Pytorch 2.6.0+cu124
Datasets 4.4.1
Tokenizers 0.22.1

Library: peft
License: apache-2.0
Created: Dec 11, 2025
Updated: Dec 12, 2025