whisper-enhanced-ml / README.md
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metadata
language:
  - hi
base_model: nurzhanit/dlc_audio
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
          args: 'config: hi, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 0

Whisper Small Hi - Sanchit Gandhi

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

  • Loss: 0.0000
  • Wer: 0.0

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: 20
  • training_steps: 500

Training results

Training Loss Epoch Step Validation Loss Wer
0.0002 50.0 50 0.0001 0.0
0.0001 100.0 100 0.0001 0.0
0.0 150.0 150 0.0000 0.0
0.0 200.0 200 0.0000 0.0
0.0 250.0 250 0.0000 0.0
0.0 300.0 300 0.0000 0.0
0.0 350.0 350 0.0000 0.0
0.0 400.0 400 0.0000 0.0
0.0 450.0 450 0.0000 0.0
0.0 500.0 500 0.0000 0.0

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.1+cu121
  • Datasets 2.15.0
  • Tokenizers 0.15.0