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---
base_model: silmi224/finetune-led-35000
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: exp2-led-risalah_data_v5
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# exp2-led-risalah_data_v5
This model is a fine-tuned version of [silmi224/finetune-led-35000](https://huggingface.co/silmi224/finetune-led-35000) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7589
- Rouge1: 26.7539
- Rouge2: 14.0212
- Rougel: 20.1731
- Rougelsum: 25.1551
## 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
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 300
- num_epochs: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 2.9869 | 1.0 | 10 | 2.6276 | 11.0083 | 2.5296 | 7.506 | 10.1145 |
| 2.8353 | 2.0 | 20 | 2.4357 | 13.1976 | 3.65 | 8.9898 | 12.4118 |
| 2.5921 | 3.0 | 30 | 2.2455 | 16.1167 | 5.4776 | 10.4243 | 14.5496 |
| 2.3757 | 4.0 | 40 | 2.1281 | 17.8354 | 6.4512 | 11.7275 | 16.9533 |
| 2.1921 | 5.0 | 50 | 2.0448 | 18.5671 | 6.3838 | 11.8151 | 16.7216 |
| 2.0619 | 6.0 | 60 | 1.9658 | 19.418 | 7.8173 | 11.8446 | 17.7673 |
| 1.9489 | 7.0 | 70 | 1.9050 | 19.6714 | 8.7398 | 11.7735 | 18.2189 |
| 1.8528 | 8.0 | 80 | 1.8411 | 20.675 | 7.8977 | 13.2651 | 19.5985 |
| 1.7631 | 9.0 | 90 | 1.8053 | 21.4919 | 8.5355 | 14.4864 | 20.2444 |
| 1.6934 | 10.0 | 100 | 1.7678 | 22.8921 | 10.0231 | 15.5104 | 21.1864 |
| 1.6315 | 11.0 | 110 | 1.7469 | 23.6054 | 10.4158 | 17.2392 | 22.3891 |
| 1.5724 | 12.0 | 120 | 1.7193 | 24.3411 | 10.8448 | 17.7772 | 22.8939 |
| 1.5203 | 13.0 | 130 | 1.7036 | 24.21 | 12.0234 | 17.3522 | 23.2189 |
| 1.4649 | 14.0 | 140 | 1.6940 | 23.8491 | 12.0368 | 17.3502 | 23.0718 |
| 1.416 | 15.0 | 150 | 1.6830 | 26.1747 | 12.5858 | 17.6622 | 25.0178 |
| 1.3721 | 16.0 | 160 | 1.6824 | 24.8559 | 12.6545 | 17.8682 | 24.0 |
| 1.3305 | 17.0 | 170 | 1.6648 | 25.7287 | 12.9393 | 18.9578 | 24.6492 |
| 1.2875 | 18.0 | 180 | 1.6513 | 23.8505 | 12.4778 | 18.1576 | 23.5659 |
| 1.246 | 19.0 | 190 | 1.6479 | 24.4501 | 12.8525 | 18.2542 | 23.6368 |
| 1.2084 | 20.0 | 200 | 1.6578 | 25.1775 | 12.5258 | 19.1736 | 24.2117 |
| 1.1673 | 21.0 | 210 | 1.6560 | 24.077 | 11.612 | 18.7053 | 22.9301 |
| 1.1305 | 22.0 | 220 | 1.6623 | 25.3731 | 12.5498 | 19.0849 | 24.5792 |
| 1.0883 | 23.0 | 230 | 1.6841 | 25.5239 | 13.1539 | 18.9111 | 24.822 |
| 1.0525 | 24.0 | 240 | 1.6613 | 25.1741 | 12.7783 | 18.5908 | 23.8229 |
| 1.0194 | 25.0 | 250 | 1.6836 | 25.3784 | 12.4683 | 18.4044 | 23.728 |
| 0.9778 | 26.0 | 260 | 1.7123 | 26.1912 | 13.5667 | 19.8968 | 25.3049 |
| 0.9443 | 27.0 | 270 | 1.7145 | 26.1743 | 14.4669 | 19.4401 | 25.6498 |
| 0.912 | 28.0 | 280 | 1.7265 | 25.2527 | 12.0503 | 18.376 | 23.9647 |
| 0.8774 | 29.0 | 290 | 1.7314 | 25.7905 | 12.9724 | 19.3096 | 24.8918 |
| 0.8425 | 30.0 | 300 | 1.7589 | 26.7539 | 14.0212 | 20.1731 | 25.1551 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1
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