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./openai/whisper-medium.en-cit-do015-wd0-lr3e-06-FULL

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

  • Loss: 0.6528
  • Wer Ortho: 32.2429
  • Wer: 22.4370

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: 3e-06
  • train_batch_size: 4
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 100
  • training_steps: 500
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Ortho Wer
1.8096 0.4773 50 1.2178 42.1611 31.5966
1.1953 0.9547 100 0.9199 37.1498 27.2773
0.9212 1.4320 150 0.8408 34.7486 25.2605
0.8448 1.9093 200 0.7837 33.6001 24.5210
0.7174 2.3866 250 0.7344 32.5039 22.9076
0.6519 2.8640 300 0.7002 33.3391 23.4958
0.5866 3.3413 350 0.6802 32.2429 22.7395
0.5625 3.8186 400 0.6631 32.6083 22.8067
0.5207 4.2959 450 0.6548 32.6779 22.8908
0.5059 4.7733 500 0.6528 32.2429 22.4370

Framework versions

  • Transformers 4.42.4
  • Pytorch 1.13.1+cu117
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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