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Whisper medium LV - Felikss Kleins

This model is a fine-tuned version of openai/whisper-medium on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1848
  • Wer: 13.5061

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: 5e-06
  • train_batch_size: 6
  • eval_batch_size: 16
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 12
  • 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
No log 0.04 200 0.8471 30.5453
1.8421 0.08 400 0.3571 27.1906
0.5851 0.12 600 0.3146 23.9508
0.4787 0.16 800 0.2913 23.2454
0.4845 0.2 1000 0.2736 20.9388
0.4845 0.24 1200 0.2495 19.1951
0.4004 0.28 1400 0.2416 18.4600
0.357 1.018 1600 0.2300 17.8576
0.3381 1.058 1800 0.2261 17.1125
0.3052 1.098 2000 0.2151 16.6013
0.3052 1.138 2200 0.2154 16.1673
0.2636 1.178 2400 0.2256 17.3107
0.2805 1.218 2600 0.2059 15.6482
0.2331 1.258 2800 0.2022 15.4599
0.2245 1.298 3000 0.1971 15.0953
0.2245 2.036 3200 0.1988 14.7604
0.2312 2.076 3400 0.1941 14.5623
0.2077 2.116 3600 0.1915 14.2175
0.1923 2.156 3800 0.1935 14.4018
0.2012 2.196 4000 0.1906 14.4850
0.2012 2.2360 4200 0.1880 13.9302
0.1694 2.276 4400 0.1860 14.1640
0.1548 3.014 4600 0.1855 13.6508
0.1628 3.054 4800 0.1850 13.5557
0.1529 3.094 5000 0.1848 13.5061

Framework versions

  • Transformers 4.45.0.dev0
  • Pytorch 2.0.1
  • Datasets 3.0.0
  • Tokenizers 0.19.1
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