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metadata
license: apache-2.0
base_model: openai/whisper-tiny
tags:
  - generated_from_keras_callback
model-index:
  - name: whisper_charsplit_new_0015
    results: []

whisper_charsplit_new_0015

This model is a fine-tuned version of openai/whisper-tiny on an unknown dataset. It achieves the following results on the evaluation set:

  • Train Loss: 0.0998
  • Train Accuracy: 0.0773
  • Train Wermet: 11.9502
  • Validation Loss: 0.3025
  • Validation Accuracy: 0.0761
  • Validation Wermet: 10.7066
  • Epoch: 14

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:

  • optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
  • training_precision: float32

Training results

Train Loss Train Accuracy Train Wermet Validation Loss Validation Accuracy Validation Wermet Epoch
0.8733 0.0602 13.0686 0.6470 0.0676 11.4066 0
0.5740 0.0666 12.7778 0.5113 0.0706 11.1022 1
0.4553 0.0692 12.2404 0.4371 0.0723 10.9105 2
0.3813 0.0708 11.9157 0.3935 0.0733 9.4615 3
0.3292 0.0720 11.5732 0.3630 0.0740 9.9885 4
0.2886 0.0729 11.5171 0.3403 0.0745 9.8042 5
0.2561 0.0736 11.3173 0.3256 0.0749 9.9431 6
0.2282 0.0743 11.7308 0.3159 0.0752 9.2086 7
0.2036 0.0748 11.4503 0.3071 0.0754 9.5236 8
0.1820 0.0754 11.7175 0.3005 0.0756 10.0755 9
0.1628 0.0758 11.7056 0.2993 0.0757 9.9497 10
0.1450 0.0762 11.7637 0.2971 0.0758 10.1481 11
0.1287 0.0766 11.8509 0.3029 0.0759 10.2042 12
0.1140 0.0770 12.1100 0.3004 0.0760 10.3873 13
0.0998 0.0773 11.9502 0.3025 0.0761 10.7066 14

Framework versions

  • Transformers 4.32.0.dev0
  • TensorFlow 2.12.0
  • Tokenizers 0.13.3