metadata

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: []

Whisper Large TH - Nonhmello

This model is a fine-tuned version of 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