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Breeze DSW Telugu - base

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

  • Loss: 0.3372
  • Wer: 37.4544

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: 32
  • eval_batch_size: 16
  • seed: 42
  • distributed_type: multi-GPU
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 2000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.2937 2.03 200 0.3237 42.5614
0.1611 5.02 400 0.2756 38.9148
0.0889 8.01 600 0.2930 38.1106
0.0456 11.0 800 0.3372 37.4544
0.0229 13.03 1000 0.3982 37.9258
0.0103 16.02 1200 0.4473 38.2678
0.0042 19.02 1400 0.4836 37.8980
0.0025 22.01 1600 0.5083 37.7317
0.002 24.04 1800 0.5220 37.8010
0.0018 27.03 2000 0.5269 37.9027

Framework versions

  • Transformers 4.37.0.dev0
  • Pytorch 2.1.2+cu121
  • Datasets 2.16.2.dev0
  • Tokenizers 0.15.0
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Evaluation results