whisper-enhanced-ml / README.md
nurzhanit's picture
End of training
4a24385 verified
metadata
language:
  - hi
base_model: nurzhanit/whisper-enhanced-ml
tags:
  - hf-asr-leaderboard
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
model-index:
  - name: Whisper Small Hi - Sanchit Gandhi
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 11.0
          type: mozilla-foundation/common_voice_11_0
          config: default
          split: None
          args: 'config: hi, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 22.35494880546075

Whisper Small Hi - Sanchit Gandhi

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

  • Loss: 0.0003
  • Wer: 22.3549

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: 50
  • training_steps: 500

Training results

Training Loss Epoch Step Validation Loss Wer
0.0035 10.0 50 0.0035 22.4403
0.0088 20.0 100 0.0033 22.3976
0.0022 30.0 150 0.0013 22.3549
0.0007 40.0 200 0.0006 22.3549
0.0005 50.0 250 0.0004 22.3549
0.0004 60.0 300 0.0004 22.3549
0.0003 70.0 350 0.0003 22.3549
0.0003 80.0 400 0.0003 22.3549
0.0003 90.0 450 0.0003 22.3549
0.0003 100.0 500 0.0003 22.3549

Framework versions

  • Transformers 4.40.0
  • Pytorch 2.5.0+cu124
  • Datasets 3.0.2
  • Tokenizers 0.19.1