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Whisper Small Malayalam - Arjun Shaji

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

  • Loss: 0.0209
  • Wer: 9.5456

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: 500
  • training_steps: 8000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.0433 0.5800 1000 0.0434 27.1379
0.02 1.1601 2000 0.0312 20.3733
0.0169 1.7401 3000 0.0242 15.4975
0.0071 2.3202 4000 0.0217 12.3555
0.0058 2.9002 5000 0.0197 11.0646
0.0022 3.4803 6000 0.0202 10.0881
0.0008 4.0603 7000 0.0204 9.7006
0.0005 4.6404 8000 0.0209 9.5456

Framework versions

  • Transformers 4.41.0
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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Evaluation results