README.md

metadata

datasets:
  - mozilla-foundation/common_voice_11_0
language:
  - th
license: apache-2.0
metrics:
  - wer
tags:
  - whisper-event
  - generated_from_trainer
model-index:
  - name: Whisper Large Thai Combined - 1000iter
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: mozilla-foundation/common_voice_11_0 th
          type: mozilla-foundation/common_voice_11_0
          config: th
          split: test
          args: th
        metrics:
          - type: wer
            value: 15.510316437482013
            name: Wer

Whisper Large Thai Combined - 1000iter

This model is a fine-tuned version of openai/whisper-large-v2 on the mozilla-foundation/common_voice_11_0 th dataset. It achieves the following results on the evaluation set:

• Loss: 0.1244
• Wer: 15.5103

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: 100
• training_steps: 5000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.1845	1.05	5000	0.1244	15.5103

Framework versions

• Transformers 4.26.0.dev0
• Pytorch 1.13.0
• Datasets 2.7.1
• Tokenizers 0.13.2