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metadata
license: apache-2.0
base_model: facebook/bart-base
tags:
  - generated_from_trainer
metrics:
  - rouge
model-index:
  - name: bart-base-summarize-finetuned
    results: []

bart-base-summarize-finetuned

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

  • Loss: 0.3408
  • Rouge1: 79.6622
  • Rouge2: 77.9282
  • Rougel: 79.6654
  • Rougelsum: 79.6384
  • Gen Len: 7.8821

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: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
No log 1.0 62 0.3856 67.6564 65.4045 67.6202 67.6206 6.6825
No log 2.0 124 0.3529 70.23 68.4349 70.2289 70.1265 6.5756
No log 3.0 186 0.3303 75.4875 73.3149 75.3918 75.3835 7.9808
No log 4.0 248 0.3165 76.17 74.0354 76.2341 76.1363 7.4435
No log 5.0 310 0.3094 76.9425 75.0561 76.9582 76.8794 7.9567
No log 6.0 372 0.3130 78.1808 76.2533 78.1846 78.1377 7.9062
No log 7.0 434 0.3081 78.5859 76.7258 78.6782 78.5825 7.6946
No log 8.0 496 0.3195 78.8452 76.85 78.8076 78.7562 8.1663
0.3758 9.0 558 0.3103 78.9204 77.2131 78.9671 78.9562 8.1341
0.3758 10.0 620 0.3091 78.7793 76.8877 78.7503 78.7031 7.7319
0.3758 11.0 682 0.3173 79.1693 77.4324 79.2141 79.1671 7.8881
0.3758 12.0 744 0.3192 79.3653 77.6962 79.4379 79.3547 7.7339
0.3758 13.0 806 0.3246 79.041 77.1587 79.1201 79.0828 7.8438
0.3758 14.0 868 0.3312 79.4605 77.7629 79.5227 79.4425 7.8014
0.3758 15.0 930 0.3300 79.7724 78.167 79.8187 79.799 7.8609
0.3758 16.0 992 0.3409 79.4618 77.694 79.4758 79.4325 7.8296
0.14 17.0 1054 0.3436 79.1169 77.3095 79.1082 79.092 8.0302
0.14 18.0 1116 0.3440 78.9896 77.2319 78.984 78.9472 7.9325
0.14 19.0 1178 0.3399 79.531 77.8083 79.5489 79.5005 7.871
0.14 20.0 1240 0.3408 79.6622 77.9282 79.6654 79.6384 7.8821

Framework versions

  • Transformers 4.41.1
  • Pytorch 1.13.1+cu117
  • Datasets 2.19.1
  • Tokenizers 0.19.1