metadata

base_model: openai/whisper-large-v3
datasets:
  - mozilla-foundation/common_voice_11_0
language:
  - th
license: apache-2.0
metrics:
  - wer
tags:
  - hf-asr-leaderboard
  - generated_from_trainer
model-index:
  - name: Whisper Large V3 Th - Chee Li
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: Common Voice 11.0
          type: mozilla-foundation/common_voice_11_0
          config: th
          split: None
          args: 'config: th split: test'
        metrics:
          - type: wer
            value: 1436.2301101591188
            name: Wer

Whisper Large V3 Th - Chee Li

This model is a fine-tuned version of openai/whisper-large-v3 on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

Loss: 0.0893
Wer: 1436.2301

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: 500
training_steps: 4000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.1636	0.3740	1000	0.1393	859.3431
0.1294	0.7479	2000	0.1121	989.6913
0.0608	1.1219	3000	0.0985	1657.8199
0.0617	1.4959	4000	0.0893	1436.2301

Framework versions

Transformers 4.42.4
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1