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bart-large-cnn-finetuned-roundup-4-8
This model is a fine-tuned version of facebook/bart-large-cnn on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7882
- Rouge1: 54.2292
- Rouge2: 37.3874
- Rougel: 40.3261
- Rougelsum: 52.2155
- Gen Len: 141.8889
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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
---|---|---|---|---|---|---|---|---|
No log | 1.0 | 398 | 0.9442 | 53.1634 | 33.7744 | 35.5688 | 50.7523 | 142.0 |
1.1285 | 2.0 | 796 | 0.8305 | 54.0713 | 35.7079 | 37.5147 | 51.6285 | 142.0 |
0.6796 | 3.0 | 1194 | 0.7735 | 52.6656 | 34.0198 | 36.8075 | 50.1502 | 142.0 |
0.4572 | 4.0 | 1592 | 0.7759 | 53.6269 | 35.4308 | 38.3735 | 51.1369 | 141.7222 |
0.4572 | 5.0 | 1990 | 0.7527 | 54.4206 | 36.0907 | 38.0818 | 51.7885 | 142.0 |
0.3171 | 6.0 | 2388 | 0.7755 | 54.9642 | 38.0459 | 41.6383 | 52.8847 | 142.0 |
0.2269 | 7.0 | 2786 | 0.7801 | 54.1637 | 35.9853 | 39.5262 | 51.6562 | 142.0 |
0.1686 | 8.0 | 3184 | 0.7882 | 54.2292 | 37.3874 | 40.3261 | 52.2155 | 141.8889 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.12.1