---
base_model: silmi224/finetune-led-35000
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: exp2-led-risalah_data_v2
  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_v2

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: 1.6223
- Rouge1: 20.4859
- Rouge2: 10.2651
- Rougel: 14.7662
- Rougelsum: 19.2553

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 3.3339        | 1.0   | 10   | 2.8010          | 8.3493  | 2.4084  | 6.4284  | 7.9202    |
| 3.1015        | 2.0   | 20   | 2.5436          | 8.9461  | 2.3615  | 6.7822  | 8.3767    |
| 2.779         | 3.0   | 30   | 2.2976          | 11.5444 | 3.5251  | 8.0258  | 10.4456   |
| 2.5118        | 4.0   | 40   | 2.1282          | 13.3666 | 4.1766  | 9.2522  | 11.9858   |
| 2.3057        | 5.0   | 50   | 2.0147          | 15.021  | 5.5582  | 10.3573 | 14.1171   |
| 2.1541        | 6.0   | 60   | 1.9283          | 15.937  | 6.8169  | 11.0627 | 14.6866   |
| 2.0326        | 7.0   | 70   | 1.8601          | 14.7364 | 5.5533  | 10.3599 | 13.9586   |
| 1.938         | 8.0   | 80   | 1.8050          | 14.8895 | 6.0535  | 9.9969  | 14.4782   |
| 1.8462        | 9.0   | 90   | 1.7492          | 14.0282 | 5.8353  | 9.232   | 13.2213   |
| 1.7767        | 10.0  | 100  | 1.7214          | 16.7779 | 7.2314  | 11.1359 | 16.1369   |
| 1.7042        | 11.0  | 110  | 1.6857          | 18.4084 | 8.7509  | 12.7906 | 17.8835   |
| 1.6543        | 12.0  | 120  | 1.6610          | 19.2909 | 8.9371  | 13.1256 | 17.6865   |
| 1.5958        | 13.0  | 130  | 1.6335          | 19.8664 | 9.7174  | 13.6907 | 18.8411   |
| 1.5414        | 14.0  | 140  | 1.6145          | 19.2112 | 9.6741  | 14.1273 | 17.7185   |
| 1.496         | 15.0  | 150  | 1.6234          | 18.8087 | 9.0827  | 13.6381 | 17.6146   |
| 1.4534        | 16.0  | 160  | 1.6035          | 19.4539 | 10.135  | 14.4283 | 18.5099   |
| 1.4177        | 17.0  | 170  | 1.5948          | 19.6367 | 10.405  | 14.0816 | 18.0333   |
| 1.3742        | 18.0  | 180  | 1.5712          | 18.8434 | 10.1431 | 13.7222 | 17.6519   |
| 1.3378        | 19.0  | 190  | 1.5829          | 18.9662 | 10.7079 | 13.9422 | 18.1457   |
| 1.3068        | 20.0  | 200  | 1.5746          | 20.724  | 11.3974 | 15.1529 | 19.8343   |
| 1.2669        | 21.0  | 210  | 1.5476          | 19.0993 | 9.6869  | 13.815  | 18.5096   |
| 1.2315        | 22.0  | 220  | 1.5606          | 20.4637 | 10.7418 | 14.634  | 19.5588   |
| 1.2005        | 23.0  | 230  | 1.5617          | 19.3271 | 9.8272  | 14.2547 | 18.5378   |
| 1.1649        | 24.0  | 240  | 1.5618          | 20.3699 | 11.3093 | 14.2115 | 19.4149   |
| 1.1344        | 25.0  | 250  | 1.5649          | 20.8124 | 11.3997 | 15.8717 | 20.0457   |
| 1.099         | 26.0  | 260  | 1.5985          | 19.8977 | 9.9926  | 14.1038 | 19.0059   |
| 1.065         | 27.0  | 270  | 1.5678          | 20.7049 | 10.9546 | 14.4462 | 19.5927   |
| 1.0344        | 28.0  | 280  | 1.6225          | 21.3939 | 11.2821 | 15.0261 | 20.3781   |
| 1.0029        | 29.0  | 290  | 1.5831          | 20.7287 | 11.0327 | 14.3893 | 19.9485   |
| 0.9711        | 30.0  | 300  | 1.6223          | 20.4859 | 10.2651 | 14.7662 | 19.2553   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1