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
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