susmitabhatt / whisper-a-nomimose-ls

huggingface.co
Total runs: 6
24-hour runs: 0
7-day runs: 0
30-day runs: 0
Model's Last Updated: November 23 2024
automatic-speech-recognition

Introduction of whisper-a-nomimose-ls

Model Details of whisper-a-nomimose-ls

whisper-a-nomimose-ls

This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0225
  • Wer: 39.3068
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: 0.0004
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 132
  • num_epochs: 11
  • mixed_precision_training: Native AMP
Training results
Training Loss Epoch Step Validation Loss Wer
0.9697 1.0 109 0.1804 43.4366
0.1049 2.0 218 0.0635 24.7050
0.0649 3.0 327 0.0376 13.4218
0.0659 4.0 436 0.0545 12.0944
0.0301 5.0 545 0.0538 23.2301
0.0382 6.0 654 0.0335 25.0737
0.0176 7.0 763 0.0253 28.9086
0.0153 8.0 872 0.0258 26.9174
0.0082 9.0 981 0.0257 51.4749
0.0054 10.0 1090 0.0222 42.5516
0.0036 10.9032 1188 0.0225 39.3068
Framework versions
  • Transformers 4.47.0.dev0
  • Pytorch 2.4.0
  • Datasets 3.0.1
  • Tokenizers 0.20.0

Runs of susmitabhatt whisper-a-nomimose-ls on huggingface.co

6
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3-day runs
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7-day runs
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