article2KW_test1.2_barthez-orangesum-title_finetuned_for_summerization
This model is a fine-tuned version of moussaKam/barthez-orangesum-title on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.1237
- Rouge1: 0.2902
- Rouge2: 0.0789
- Rougel: 0.2899
- Rougelsum: 0.2894
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: 5.6e-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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 1.6441 | 1.0 | 1497 | 1.2902 | 0.2652 | 0.0690 | 0.2647 | 0.2644 |
| 1.1997 | 2.0 | 2994 | 1.1705 | 0.2854 | 0.0685 | 0.2858 | 0.2850 |
| 1.0398 | 3.0 | 4491 | 1.1237 | 0.2902 | 0.0789 | 0.2899 | 0.2894 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.11.0
- Datasets 2.3.2
- Tokenizers 0.11.0