README.md

metadata

language:
  - th
license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
base_model: openai/whisper-small
model-index:
  - name: Whisper Small Thai Combined Concat
    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: 27.279438445464898
            name: Wer

Whisper Small Thai Combined Concat

This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_11_0 th dataset and additional scraped data. It achieves the following results on the evaluation set:

• Loss: 0.5034
• Wer: 27.2794 (without tokenizer)

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: 64
• eval_batch_size: 32
• seed: 42
• distributed_type: multi-GPU
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• training_steps: 5000

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0002	83.33	5000	0.5034	27.2794

Framework versions

• Transformers 4.27.0.dev0
• Pytorch 1.13.1
• Datasets 2.9.1.dev0
• Tokenizers 0.13.2