finetunedsmall / README.md
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metadata
language:
  - en
license: mit
base_model: distil-whisper/distil-small.en
tags:
  - hf-asr-leaderboard
  - generated_from_trainer
datasets:
  - vision
  - finetuneasr
metrics:
  - wer
model-index:
  - name: ThangaTharun/finetunedsmall
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: ThangaTharun/Barishka2
          type: vision
        metrics:
          - name: Wer
            type: wer
            value: 5.47945205479452

ThangaTharun/finetunedsmall

This model is a fine-tuned version of distil-whisper/distil-small.en on the ThangaTharun/Barishka2 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0136
  • Wer: 5.4795

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: 1
  • training_steps: 60
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
3.1327 1.25 5 2.6560 47.9452
1.7171 2.5 10 1.7472 26.0274
1.0789 3.75 15 0.9175 12.3288
0.0999 5.0 20 0.1663 13.6986
0.0173 6.25 25 0.0855 13.6986
0.004 7.5 30 0.0366 9.5890
0.0017 8.75 35 0.0216 6.8493
0.0008 10.0 40 0.0165 6.8493
0.0005 11.25 45 0.0146 5.4795
0.0005 12.5 50 0.0138 5.4795
0.0005 13.75 55 0.0136 5.4795
0.0004 15.0 60 0.0136 5.4795

Framework versions

  • Transformers 4.36.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.0