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Whisper Base - Kiran Pantha

This model is a fine-tuned version of openai/whisper-base on the OpenSLR54 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2056
  • Wer: 43.2821

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: 8
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 5000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.5029 0.0750 500 0.4922 77.0205
0.351 0.1499 1000 0.3561 65.6941
0.3034 0.2249 1500 0.2988 57.0618
0.2689 0.2999 2000 0.2714 53.2844
0.2584 0.3749 2500 0.2537 50.8369
0.2325 0.4498 3000 0.2393 48.0282
0.2238 0.5248 3500 0.2271 46.5723
0.2149 0.5998 4000 0.2149 44.4056
0.2038 0.6748 4500 0.2091 43.6834
0.2026 0.7497 5000 0.2056 43.2821

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.0+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1
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