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Whisper Tiny Hebrew

This model is a fine-tuned version of openai/whisper-tiny on the ivrit-ai/whisper-training dataset.

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: 10000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.973 0.13 500 0.8480 77.6213
0.9024 0.25 1000 0.7710 67.9838
0.8049 0.38 1500 0.7499 66.7384
0.7221 0.5 2000 0.7092 64.7953
0.7464 0.63 2500 0.6939 62.7543
0.7396 0.75 3000 0.6839 62.5261
0.7336 0.88 3500 0.6716 61.2350
0.6118 1.01 4000 0.6512 58.4637
0.6299 1.13 4500 0.6564 60.1721
0.6318 1.26 5000 0.6475 58.8550
0.6315 1.38 5500 0.6361 58.9724
0.6081 1.51 6000 0.6321 57.1596
0.6487 1.63 6500 0.6459 58.5616
0.6481 1.76 7000 0.6298 56.9379
0.5833 1.88 7500 0.6303 57.8965
0.5689 2.01 8000 0.6305 56.1750
0.5223 2.14 8500 0.6335 56.6967
0.574 2.26 9000 0.6248 55.3730
0.5841 2.39 9500 0.6320 55.6273
0.5533 2.51 10000 0.6254 55.8816

Framework versions

  • Transformers 4.40.0.dev0
  • Pytorch 2.2.1
  • Datasets 2.18.0
  • Tokenizers 0.15.2
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Evaluation results