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bart-large-cnn-samsum-whole_summary_chatGPT_and_tweetsum
This model is a fine-tuned version of philschmid/bart-large-cnn-samsum on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 5.1747
- Rouge1: 22.1238
- Rouge2: 7.5755
- Rougel: 15.8539
- Rougelsum: 18.8483
- Gen Len: 62.2
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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 397 | 2.3879 | 19.7449 | 8.1533 | 16.4998 | 17.8335 | 62.0 |
| 1.9889 | 2.0 | 794 | 2.6982 | 21.8787 | 12.2713 | 19.5273 | 19.3784 | 63.6 |
| 1.0298 | 3.0 | 1191 | 2.8150 | 20.3414 | 9.8563 | 16.7994 | 16.7994 | 61.0 |
| 0.52 | 4.0 | 1588 | 3.2921 | 19.5424 | 7.94 | 15.3118 | 17.1955 | 60.8 |
| 0.52 | 5.0 | 1985 | 3.4467 | 17.0802 | 5.6269 | 13.365 | 13.365 | 61.8 |
| 0.3114 | 6.0 | 2382 | 4.3416 | 23.5849 | 10.5415 | 17.8904 | 19.7952 | 59.2 |
| 0.1644 | 7.0 | 2779 | 4.7510 | 20.4712 | 8.7588 | 15.7973 | 18.1441 | 61.8 |
| 0.0814 | 8.0 | 3176 | 4.5738 | 22.4661 | 8.1775 | 15.6491 | 16.9007 | 60.0 |
| 0.045 | 9.0 | 3573 | 5.1804 | 23.1379 | 7.3984 | 16.6129 | 17.7338 | 62.6 |
| 0.045 | 10.0 | 3970 | 5.1747 | 22.1238 | 7.5755 | 15.8539 | 18.8483 | 62.2 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.12.1
- Datasets 2.6.1
- Tokenizers 0.12.1
