whisper-small-km / README.md
ksoky's picture
Update README.md
e81738b
metadata
language:
  - km
license: apache-2.0
tags:
  - hf-asr-leaderboard
  - generated_from_trainer
datasets:
  - openslr
metrics:
  - wer
model-index:
  - name: Whisper Small Km - Kak Soky
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: SLR42
          type: openslr
          args: 'config: km, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 35.665399239543724

Whisper Small Km - Kak Soky

This model is a fine-tuned version of openai/whisper-small on the SLR42 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1471
  • Wer: 35.6654

Model description

The model was fine-tuned on both encoder-decoder of transformer-based.

Intended uses & limitations

The training data is limited, thus the performance is also limited to only reading speech and a limited domain (tourism).

Training and evaluation data

The training and evaluation data was split in a 9:1 ratio from Google Text-to-speech corpus.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 1e-05
  • train_batch_size: 2
  • eval_batch_size: 4
  • 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
0.3639 0.76 1000 0.3452 71.9392
0.1553 1.53 2000 0.2025 49.0494
0.0565 2.29 3000 0.1664 39.9240
0.0334 3.06 4000 0.1471 35.6654

Framework versions

  • Transformers 4.25.0.dev0
  • Pytorch 1.12.1+cu113
  • Datasets 2.7.0
  • Tokenizers 0.13.2