whisper-enhanced-ml / README.md
nurzhanit's picture
End of training
93a8568 verified
|
raw
history blame
2.41 kB
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: 0.0010
  • 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
1.3416 10.0 50 0.7715 69.5819
0.1814 20.0 100 0.0861 33.4898
0.0174 30.0 150 0.0096 22.3549
0.0038 40.0 200 0.0029 22.3549
0.0022 50.0 250 0.0019 22.3549
0.0016 60.0 300 0.0015 22.3549
0.0013 70.0 350 0.0012 22.3549
0.0012 80.0 400 0.0011 22.3549
0.0011 90.0 450 0.0010 22.3549
0.001 100.0 500 0.0010 22.3549

Framework versions

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