PTS-Bart-Large-CNN
This model is a fine-tuned version of facebook/bart-large-cnn on the PTS dataset. It achieves the following results on the evaluation set:
- Loss: 1.1760
- Rouge1: 0.6551
- Rouge2: 0.4332
- Rougel: 0.5543
- Rougelsum: 0.5541
- Gen Len: 80.0886
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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 | 220 | 0.8239 | 0.6263 | 0.3973 | 0.5238 | 0.5237 | 84.2023 |
No log | 2.0 | 440 | 0.8201 | 0.6461 | 0.4184 | 0.5417 | 0.5416 | 81.1659 |
0.7121 | 3.0 | 660 | 0.8661 | 0.6479 | 0.4226 | 0.5448 | 0.5454 | 80.5409 |
0.7121 | 4.0 | 880 | 0.9784 | 0.6474 | 0.4242 | 0.5424 | 0.5425 | 82.2932 |
0.2619 | 5.0 | 1100 | 1.0645 | 0.655 | 0.4327 | 0.5517 | 0.5517 | 80.8386 |
0.2619 | 6.0 | 1320 | 1.1098 | 0.6548 | 0.4339 | 0.5542 | 0.5543 | 81.3545 |
0.1124 | 7.0 | 1540 | 1.1528 | 0.6528 | 0.4298 | 0.5511 | 0.551 | 80.5705 |
0.1124 | 8.0 | 1760 | 1.1760 | 0.6551 | 0.4332 | 0.5543 | 0.5541 | 80.0886 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Base model
facebook/bart-large-cnn
Finetuned
this model
Dataset used to train ahmedmbutt/PTS-Bart-Large-CNN
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Evaluation results
- Rouge1 on PTS Datasetself-reported0.655
- Rouge2 on PTS Datasetself-reported0.433
- Rougel on PTS Datasetself-reported0.554
- Rougelsum on PTS Datasetself-reported0.554