metadata
base_model: silmi224/finetune-led-35000
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: led-risalah_data_v17_2
results: []
led-risalah_data_v17_2
This model is a fine-tuned version of silmi224/finetune-led-35000 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.6183
- Rouge1: 24.9438
- Rouge2: 12.823
- Rougel: 19.4874
- Rougelsum: 23.9852
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: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 400
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 3.0463 | 1.0 | 20 | 2.6201 | 10.5455 | 3.3808 | 8.0147 | 9.7658 |
| 2.7524 | 2.0 | 40 | 2.3724 | 13.2211 | 4.2659 | 9.4319 | 11.4823 |
| 2.4437 | 3.0 | 60 | 2.1687 | 15.9732 | 4.6109 | 10.6226 | 14.1832 |
| 2.1607 | 4.0 | 80 | 2.0550 | 17.731 | 6.3571 | 10.6519 | 16.6744 |
| 2.0465 | 5.0 | 100 | 1.9641 | 19.3209 | 6.788 | 12.3334 | 17.2773 |
| 1.8932 | 6.0 | 120 | 1.8951 | 20.2099 | 9.1781 | 14.4373 | 18.5711 |
| 1.8485 | 7.0 | 140 | 1.8391 | 17.9081 | 7.2188 | 12.0437 | 16.1709 |
| 1.7211 | 8.0 | 160 | 1.7814 | 20.2991 | 8.2239 | 13.6757 | 18.9692 |
| 1.6461 | 9.0 | 180 | 1.7475 | 25.3547 | 10.5964 | 16.5484 | 23.7821 |
| 1.6109 | 10.0 | 200 | 1.7211 | 22.2062 | 9.3952 | 15.2277 | 21.1163 |
| 1.5818 | 11.0 | 220 | 1.7049 | 22.8022 | 9.2525 | 15.8587 | 21.4785 |
| 1.5194 | 12.0 | 240 | 1.6829 | 23.9497 | 11.1116 | 16.8015 | 22.8818 |
| 1.4541 | 13.0 | 260 | 1.6700 | 23.3403 | 11.4888 | 16.9861 | 22.4228 |
| 1.3816 | 14.0 | 280 | 1.6555 | 25.8179 | 13.2041 | 17.7017 | 24.7336 |
| 1.3908 | 15.0 | 300 | 1.6451 | 25.697 | 13.4504 | 18.41 | 24.7942 |
| 1.364 | 16.0 | 320 | 1.6224 | 25.7576 | 11.9706 | 17.695 | 24.2206 |
| 1.2521 | 17.0 | 340 | 1.6094 | 24.1556 | 12.942 | 18.5932 | 23.2197 |
| 1.2384 | 18.0 | 360 | 1.6041 | 25.1035 | 12.7288 | 18.2081 | 24.4216 |
| 1.2734 | 19.0 | 380 | 1.6075 | 25.482 | 13.4025 | 19.7018 | 25.1256 |
| 1.1228 | 20.0 | 400 | 1.6183 | 24.9438 | 12.823 | 19.4874 | 23.9852 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1