bart-text-simplification_1e4_adafactor_newsela
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: 0.5221
- Rouge1: 53.696
- Rouge2: 36.5456
- Rougel: 50.0629
- Rougelsum: 50.0673
- Gen Len: 18.558
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: 128
- eval_batch_size: 128
- 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 |
---|---|---|---|---|---|---|---|---|
0.7479 | 1.0 | 803 | 0.3428 | 55.7433 | 39.7505 | 52.5585 | 52.6043 | 18.5474 |
0.2505 | 2.0 | 1606 | 0.3552 | 54.8713 | 38.517 | 51.9121 | 51.9413 | 18.4364 |
0.213 | 3.0 | 2409 | 0.3733 | 55.0367 | 38.8217 | 51.5907 | 51.6237 | 18.8225 |
0.167 | 4.0 | 3212 | 0.3933 | 55.0962 | 38.7575 | 51.9311 | 51.9376 | 18.7433 |
0.1412 | 5.0 | 4015 | 0.4097 | 54.8308 | 38.2353 | 51.5186 | 51.5117 | 18.611 |
0.1193 | 6.0 | 4818 | 0.4258 | 53.8669 | 37.2692 | 50.4845 | 50.4928 | 18.6443 |
0.1039 | 7.0 | 5621 | 0.4395 | 54.1498 | 37.7107 | 50.9405 | 50.9451 | 18.5728 |
0.0928 | 8.0 | 6424 | 0.4502 | 53.9131 | 37.1201 | 50.6696 | 50.6776 | 18.5488 |
0.0801 | 9.0 | 7227 | 0.4594 | 53.8123 | 37.0674 | 50.4964 | 50.4957 | 18.4986 |
0.0734 | 10.0 | 8030 | 0.4733 | 53.8377 | 36.8825 | 50.3857 | 50.3775 | 18.4569 |
0.0648 | 11.0 | 8833 | 0.4747 | 53.3192 | 36.0006 | 49.724 | 49.7651 | 18.4844 |
0.0601 | 12.0 | 9636 | 0.4888 | 54.0952 | 36.8581 | 50.6073 | 50.6233 | 18.5714 |
0.0558 | 13.0 | 10439 | 0.4903 | 53.2469 | 36.1195 | 49.7181 | 49.7835 | 18.4123 |
0.0506 | 14.0 | 11242 | 0.4987 | 53.3193 | 36.3095 | 49.7999 | 49.8537 | 18.4958 |
0.0484 | 15.0 | 12045 | 0.5051 | 53.297 | 36.1379 | 49.5479 | 49.5797 | 18.4144 |
0.0444 | 16.0 | 12848 | 0.5134 | 53.696 | 36.768 | 50.0134 | 50.0706 | 18.5813 |
0.042 | 17.0 | 13651 | 0.5162 | 53.4729 | 36.5564 | 49.8635 | 49.8709 | 18.5269 |
0.0404 | 18.0 | 14454 | 0.5165 | 53.5562 | 36.4654 | 49.9419 | 49.9367 | 18.524 |
0.0376 | 19.0 | 15257 | 0.5195 | 53.3768 | 36.359 | 49.7394 | 49.7357 | 18.5877 |
0.0365 | 20.0 | 16060 | 0.5221 | 53.696 | 36.5456 | 50.0629 | 50.0673 | 18.558 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
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