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Breeze DSW Tamil - base

This model is a fine-tuned version of openai/whisper-base on the mozilla-foundation/common_voice_16_0 ta dataset. It achieves the following results on the evaluation set:

  • Loss: 0.375
  • Wer: 21.4071

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: 1000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.1698 0.1 100 0.5723 30.4406
0.3578 0.2 200 0.4302 25.6862
0.2832 0.3 300 0.3967 23.2048
0.2663 0.4 400 0.4038 23.8525
0.5175 0.5 500 0.3962 24.1466
0.2365 0.6 600 0.3850 22.2595
0.1692 0.7 700 0.3960 21.8687
0.1815 0.8 800 0.3823 22.0772
0.1612 0.9 900 0.3701 21.8056
0.1393 1.0 1000 0.375 21.4071

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