README.md

metadata

language:
  - hre
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - ntviet/hre-audio-dataset2
metrics:
  - wer
model-index:
  - name: Whisper Small for Hre - NT Viet
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Hre audio dataset 2
          type: ntviet/hre-audio-dataset2
          config: default
          split: test
          args: default
        metrics:
          - name: Wer
            type: wer
            value: 78.35820895522389

Whisper Small for Hre - NT Viet

This model is a fine-tuned version of openai/whisper-small on the Hre audio dataset 2 dataset. It achieves the following results on the evaluation set:

• Loss: 2.5265
• Wer Ortho: 78.0303
• Wer: 78.3582

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: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: constant_with_warmup
• lr_scheduler_warmup_steps: 50
• training_steps: 500
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
0.086	4.13	500	2.5265	78.0303	78.3582

Framework versions

• Transformers 4.38.2
• Pytorch 2.1.0+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2