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bart-large-finetuned-bart
This model is a fine-tuned version of facebook/bart-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8644
- Rouge1: 80.883
- Rouge2: 72.0268
- Rougel: 77.0146
- Rougelsum: 77.3408
- Gen Len: 19.2969
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: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 12 | 0.8158 | 70.5188 | 55.0313 | 61.668 | 62.0697 | 18.8281 |
| No log | 2.0 | 24 | 0.6610 | 78.9718 | 67.9238 | 71.2508 | 71.5416 | 19.2188 |
| No log | 3.0 | 36 | 0.6257 | 79.2603 | 69.4298 | 73.031 | 73.4136 | 19.1875 |
| No log | 4.0 | 48 | 0.6354 | 79.0425 | 69.7772 | 73.6893 | 73.8356 | 19.3125 |
| No log | 5.0 | 60 | 0.6126 | 79.9003 | 69.6148 | 73.3622 | 73.7154 | 19.2656 |
| No log | 6.0 | 72 | 0.6537 | 80.0209 | 69.9125 | 73.6876 | 73.9664 | 19.1875 |
| No log | 7.0 | 84 | 0.7168 | 80.7559 | 71.8251 | 75.5574 | 75.6627 | 19.2031 |
| No log | 8.0 | 96 | 0.6980 | 80.9116 | 72.2951 | 75.9015 | 76.2205 | 19.2656 |
| No log | 9.0 | 108 | 0.7569 | 80.1034 | 70.8352 | 75.1723 | 75.4102 | 19.25 |
| No log | 10.0 | 120 | 0.7523 | 80.0436 | 71.0855 | 75.8337 | 76.1002 | 19.3281 |
| No log | 11.0 | 132 | 0.7742 | 80.5982 | 71.713 | 75.9081 | 76.1564 | 19.4375 |
| No log | 12.0 | 144 | 0.7570 | 79.4243 | 70.5775 | 75.3521 | 75.9334 | 19.4844 |
| No log | 13.0 | 156 | 0.8225 | 80.2529 | 72.6598 | 76.6931 | 76.8326 | 19.7344 |
| No log | 14.0 | 168 | 0.8696 | 79.821 | 71.2369 | 75.836 | 76.0734 | 19.4688 |
| No log | 15.0 | 180 | 0.8820 | 80.9234 | 72.5022 | 76.7848 | 77.0368 | 19.375 |
| No log | 16.0 | 192 | 0.8400 | 80.5926 | 72.0275 | 76.8664 | 77.0773 | 19.2969 |
| No log | 17.0 | 204 | 0.8461 | 80.6004 | 72.2808 | 76.8693 | 77.0517 | 19.375 |
| No log | 18.0 | 216 | 0.8577 | 81.0069 | 73.1954 | 77.467 | 77.7083 | 19.3906 |
| No log | 19.0 | 228 | 0.8695 | 81.0333 | 72.5324 | 77.4248 | 77.5971 | 19.2969 |
| No log | 20.0 | 240 | 0.8644 | 80.883 | 72.0268 | 77.0146 | 77.3408 | 19.2969 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
