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---
base_model: silmi224/finetune-led-35000
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: led-risalah_data_v17_3
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. -->
# led-risalah_data_v17_3
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: 1.6551
- Rouge1: 25.33
- Rouge2: 12.4758
- Rougel: 18.3801
- Rougelsum: 24.0275
## 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: 200
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 2.9826 | 1.0 | 20 | 2.5250 | 11.8736 | 3.4553 | 8.0701 | 10.4233 |
| 2.5516 | 2.0 | 40 | 2.2001 | 15.7664 | 5.0213 | 10.8555 | 14.1975 |
| 2.2334 | 3.0 | 60 | 2.0424 | 17.0425 | 6.006 | 10.956 | 15.2795 |
| 1.9577 | 4.0 | 80 | 1.9305 | 19.1792 | 7.6754 | 12.651 | 17.7519 |
| 1.8602 | 5.0 | 100 | 1.8351 | 22.4846 | 8.3095 | 14.0022 | 20.587 |
| 1.702 | 6.0 | 120 | 1.7809 | 21.9395 | 8.5042 | 14.9427 | 20.3436 |
| 1.6525 | 7.0 | 140 | 1.7286 | 23.7825 | 10.9231 | 15.9319 | 22.0902 |
| 1.5285 | 8.0 | 160 | 1.6839 | 24.1286 | 11.2382 | 16.7057 | 22.3731 |
| 1.4623 | 9.0 | 180 | 1.6644 | 23.8767 | 12.3834 | 17.5761 | 22.6869 |
| 1.4175 | 10.0 | 200 | 1.6551 | 25.33 | 12.4758 | 18.3801 | 24.0275 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1
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