Jan van Doorn
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metadata
license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: whisper-large-v2-atco2-asr-atcosim
    results: []

whisper-large-v2-atco2-asr-atcosim

This model is a fine-tuned version of openai/whisper-large-v2 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1063
  • Wer: 5.5528

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
  • distributed_type: multi-GPU
  • num_devices: 4
  • total_train_batch_size: 64
  • total_eval_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 250
  • training_steps: 12644

Training results

Training Loss Epoch Step Validation Loss Wer
0.0503 1.97 250 0.0602 8.5346
0.0172 3.94 500 0.0602 4.1352
0.0084 5.91 750 0.0608 3.3803
0.0046 7.87 1000 0.0624 3.5523
0.0024 9.84 1250 0.0635 3.5774
0.0019 11.81 1500 0.0704 4.0933
0.0019 13.78 1750 0.0712 6.3832
0.0026 15.75 2000 0.0677 3.3635
0.0016 17.72 2250 0.0706 3.2000
0.0009 19.69 2500 0.0709 4.0597
0.0003 21.65 2750 0.0735 3.2922
0.0001 23.62 3000 0.0771 3.8836
0.0001 25.59 3250 0.0791 4.0178
0.0001 27.56 3500 0.0804 3.7913
0.0002 29.53 3750 0.0792 4.0597
0.0 31.5 4000 0.0831 4.1059
0.0 33.46 4250 0.0847 3.9507
0.0 35.43 4500 0.0859 4.1059
0.0 37.4 4750 0.0871 4.1688
0.0 39.37 5000 0.0883 4.2820
0.0 41.34 5250 0.0891 4.3449
0.0 43.31 5500 0.0898 4.5378
0.0 45.28 5750 0.0908 4.5546
0.0 47.24 6000 0.0915 4.7433
0.0 49.21 6250 0.0923 4.7643
0.0 51.18 6500 0.0933 4.8146
0.0 53.15 6750 0.0939 4.7140
0.0 55.12 7000 0.0947 4.7475
0.0 57.09 7250 0.0955 4.7266
0.0 59.06 7500 0.0962 4.8188
0.0 61.02 7750 0.0969 4.8775
0.0 62.99 8000 0.0976 5.0159
0.0 64.96 8250 0.0982 5.0872
0.0 66.93 8500 0.0989 5.1669
0.0 68.9 8750 0.0996 5.1208
0.0 70.87 9000 0.1002 5.1795
0.0 72.83 9250 0.1009 5.2969
0.0 74.8 9500 0.1014 5.2969
0.0 76.77 9750 0.1020 5.3892
0.0 78.74 10000 0.1027 5.4269
0.0 80.71 10250 0.1031 5.3431
0.0 82.68 10500 0.1038 5.4479
0.0 84.65 10750 0.1043 5.4940
0.0 86.61 11000 0.1047 5.4563
0.0 88.58 11250 0.1052 5.4857
0.0 90.55 11500 0.1055 5.4857
0.0 92.52 11750 0.1058 5.5024
0.0 94.49 12000 0.1060 5.5108
0.0 96.46 12250 0.1062 5.5150
0.0 98.43 12500 0.1063 5.5528

Framework versions

  • Transformers 4.30.0.dev0
  • Pytorch 2.0.1+cu117
  • Datasets 2.12.0
  • Tokenizers 0.13.3