whisper-omg-2 / README.md
nurzhanit's picture
End of training
82e5fbe 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: 0

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: 0.0001
  • 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: 50
  • training_steps: 1000

Training results

Training Loss Epoch Step Validation Loss Wer
0.0417 0.8475 50 0.0308 2.8184
0.0233 1.6949 100 0.0178 2.0473
0.0153 2.5424 150 0.0104 1.5953
0.0121 3.3898 200 0.0056 1.3560
0.0055 4.2373 250 0.0039 0.8508
0.0061 5.0847 300 0.0022 0.3457
0.0026 5.9322 350 0.0012 0.2127
0.0018 6.7797 400 0.0008 0.0798
0.0015 7.6271 450 0.0006 0.1595
0.0009 8.4746 500 0.0005 0.0266
0.0004 9.3220 550 0.0003 0.0266
0.0003 10.1695 600 0.0002 0.0
0.0002 11.0169 650 0.0003 0.0266
0.0002 11.8644 700 0.0002 0.0266
0.0002 12.7119 750 0.0002 0.0
0.0002 13.5593 800 0.0002 0.0
0.0002 14.4068 850 0.0002 0.0
0.0002 15.2542 900 0.0002 0.0
0.0001 16.1017 950 0.0001 0.0
0.0002 16.9492 1000 0.0001 0.0

Framework versions

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