bart-text-simplification_1e4_adafactor_biendata
This model is a fine-tuned version of facebook/bart-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7599
- Rouge1: 29.7176
- Rouge2: 10.9512
- Rougel: 25.5101
- Rougelsum: 25.526
- Gen Len: 15.2029
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: 0.0001
- 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
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
---|---|---|---|---|---|---|---|---|
No log | 1.0 | 232 | 0.5813 | 30.604 | 12.4253 | 26.5172 | 26.4807 | 15.2241 |
No log | 2.0 | 464 | 0.5739 | 31.9076 | 12.798 | 27.4728 | 27.4929 | 15.2241 |
1.0176 | 3.0 | 696 | 0.5700 | 31.3776 | 12.2852 | 27.1116 | 27.0878 | 15.6459 |
1.0176 | 4.0 | 928 | 0.5762 | 30.8731 | 12.3014 | 26.9196 | 26.8301 | 14.6353 |
0.4798 | 5.0 | 1160 | 0.5863 | 29.927 | 11.7166 | 25.9447 | 25.921 | 14.4297 |
0.4798 | 6.0 | 1392 | 0.6003 | 29.9528 | 11.2098 | 25.6908 | 25.7209 | 14.7414 |
0.3855 | 7.0 | 1624 | 0.6179 | 30.1161 | 11.2863 | 26.1433 | 26.1519 | 15.1698 |
0.3855 | 8.0 | 1856 | 0.6290 | 29.5566 | 11.1229 | 25.6003 | 25.5754 | 14.87 |
0.3092 | 9.0 | 2088 | 0.6538 | 29.7844 | 11.2434 | 25.8222 | 25.8067 | 14.9708 |
0.3092 | 10.0 | 2320 | 0.6698 | 28.9941 | 10.6603 | 25.0054 | 25.0198 | 15.0239 |
0.247 | 11.0 | 2552 | 0.6906 | 28.732 | 10.4525 | 24.8897 | 24.8953 | 14.9721 |
0.247 | 12.0 | 2784 | 0.7023 | 29.0609 | 10.4762 | 24.9678 | 24.9893 | 15.317 |
0.198 | 13.0 | 3016 | 0.7200 | 29.9516 | 11.2397 | 25.7347 | 25.7489 | 15.1485 |
0.198 | 14.0 | 3248 | 0.7263 | 29.1565 | 10.7363 | 25.2238 | 25.203 | 14.9761 |
0.198 | 15.0 | 3480 | 0.7376 | 30.0068 | 11.2078 | 26.0012 | 26.0235 | 14.9589 |
0.1602 | 16.0 | 3712 | 0.7489 | 29.8747 | 11.0555 | 25.7321 | 25.7543 | 15.2931 |
0.1602 | 17.0 | 3944 | 0.7487 | 29.6901 | 10.8692 | 25.5467 | 25.5808 | 15.2798 |
0.1342 | 18.0 | 4176 | 0.7553 | 29.5496 | 10.8611 | 25.2895 | 25.3218 | 15.3156 |
0.1342 | 19.0 | 4408 | 0.7590 | 29.7733 | 11.1577 | 25.671 | 25.6883 | 15.1313 |
0.1184 | 20.0 | 4640 | 0.7599 | 29.7176 | 10.9512 | 25.5101 | 25.526 | 15.2029 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
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