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Upload TFWhisperForConditionalGeneration
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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_round2__0017
    results: []

whisper_charsplit_new_round2__0017

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: 0.0005
  • Train Accuracy: 0.0795
  • Train Wermet: 9.0553
  • Validation Loss: 0.5620
  • Validation Accuracy: 0.0768
  • Validation Wermet: 8.5020
  • Epoch: 16

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
0.0010 0.0795 8.7507 0.5575 0.0767 7.6778 0
0.0013 0.0795 8.9468 0.5652 0.0766 8.3360 1
0.0025 0.0795 8.7338 0.5673 0.0765 8.3770 2
0.0019 0.0795 8.9450 0.5623 0.0766 7.7117 3
0.0011 0.0795 8.9053 0.5609 0.0767 7.5155 4
0.0012 0.0795 8.8862 0.5667 0.0767 8.2913 5
0.0009 0.0795 8.7510 0.5642 0.0766 7.9083 6
0.0037 0.0795 9.3428 0.5717 0.0764 8.2631 7
0.0031 0.0795 9.2135 0.5636 0.0766 8.2384 8
0.0011 0.0795 8.9730 0.5605 0.0767 8.3958 9
0.0005 0.0795 9.3749 0.5552 0.0768 8.0800 10
0.0003 0.0795 9.3340 0.5584 0.0768 8.1322 11
0.0005 0.0795 9.2292 0.5687 0.0767 8.5576 12
0.0037 0.0795 9.2838 0.5751 0.0765 7.4189 13
0.0038 0.0795 8.7270 0.5605 0.0767 7.7098 14
0.0012 0.0795 8.8259 0.5563 0.0768 8.2647 15
0.0005 0.0795 9.0553 0.5620 0.0768 8.5020 16

Framework versions

  • Transformers 4.32.0.dev0
  • TensorFlow 2.12.0
  • Tokenizers 0.13.3