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video_transcript_summary

Text2Text Generation
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bart
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video_transcript_summary / README.md
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metadata
license: mit
base_model: facebook/bart-large-cnn
tags:
  - generated_from_trainer
metrics:
  - rouge
model-index:
  - name: video_transcript_summary
    results: []

video_transcript_summary

This model is a fine-tuned version of facebook/bart-large-cnn on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 5.5472
  • Rouge1: 0.3909
  • Rouge2: 0.1328
  • Rougel: 0.2802
  • Rougelsum: 0.2801
  • Gen Len: 69.8235

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: 2e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 100
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
No log 1.0 5 2.6381 0.3163 0.0838 0.2135 0.2138 72.1176
No log 2.0 10 2.4739 0.345 0.0969 0.2372 0.2364 69.7647
No log 3.0 15 2.6011 0.3719 0.116 0.2619 0.2605 69.7059
No log 4.0 20 2.7476 0.3769 0.1156 0.2588 0.2572 72.9412
No log 5.0 25 2.9283 0.3812 0.1206 0.2645 0.2625 74.4706
No log 6.0 30 3.3089 0.3722 0.1194 0.2779 0.2769 70.1765
No log 7.0 35 3.6585 0.3802 0.1177 0.2718 0.2719 73.2941
No log 8.0 40 3.8924 0.3764 0.1056 0.2661 0.2651 70.8235
No log 9.0 45 4.3638 0.3677 0.1144 0.2653 0.2634 74.0
No log 10.0 50 4.5590 0.354 0.1069 0.2491 0.2477 71.0
No log 11.0 55 4.5746 0.4103 0.1359 0.2935 0.293 72.5882
No log 12.0 60 4.9055 0.3869 0.118 0.2705 0.2695 66.1176
No log 13.0 65 5.0987 0.3947 0.1292 0.2713 0.2716 74.7647
No log 14.0 70 5.3199 0.3814 0.1135 0.2839 0.2816 72.2353
No log 15.0 75 5.4462 0.4092 0.1265 0.2896 0.29 68.0
No log 16.0 80 5.4262 0.412 0.1282 0.293 0.2932 72.0
No log 17.0 85 5.4873 0.3776 0.1051 0.2637 0.2636 68.8824
No log 18.0 90 5.6043 0.3932 0.1106 0.2734 0.2727 67.9412
No log 19.0 95 5.7495 0.3694 0.1075 0.2699 0.2692 69.7647
No log 20.0 100 5.6518 0.3849 0.1109 0.2714 0.2709 65.5882
No log 21.0 105 5.4524 0.3762 0.1101 0.2598 0.2596 64.5294
No log 22.0 110 5.5472 0.3909 0.1328 0.2802 0.2801 69.8235

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.1+cu118
  • Datasets 2.20.0
  • Tokenizers 0.19.1