---
base_model: silmi224/finetune-led-35000
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: exp2-led-risalah_data_v7-fix
  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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/silmiaulia/huggingface/runs/2a3srq9p)
# exp2-led-risalah_data_v7-fix

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: 1.6801
- Rouge1: 20.0364
- Rouge2: 9.57
- Rougel: 13.9743
- Rougelsum: 14.0563

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 3.8706        | 1.0   | 10   | 3.3282          | 9.2634  | 1.825  | 6.2857  | 6.6749    |
| 3.5173        | 2.0   | 20   | 2.8713          | 9.381   | 1.5365 | 6.5965  | 6.6722    |
| 3.0587        | 3.0   | 30   | 2.5101          | 12.3761 | 3.5034 | 8.6155  | 8.7913    |
| 2.7254        | 4.0   | 40   | 2.2919          | 14.8916 | 4.9071 | 10.0    | 9.9487    |
| 2.504         | 5.0   | 50   | 2.1490          | 14.5316 | 4.9407 | 9.6973  | 9.5973    |
| 2.3306        | 6.0   | 60   | 2.0516          | 15.6234 | 5.419  | 10.6929 | 10.671    |
| 2.1991        | 7.0   | 70   | 1.9705          | 16.9222 | 6.1531 | 10.3785 | 10.4171   |
| 2.0922        | 8.0   | 80   | 1.9114          | 15.9531 | 6.007  | 10.2455 | 10.2734   |
| 2.0108        | 9.0   | 90   | 1.8601          | 16.3146 | 6.2786 | 10.632  | 10.6027   |
| 1.9243        | 10.0  | 100  | 1.8352          | 18.1771 | 6.6919 | 11.1811 | 11.2366   |
| 1.8675        | 11.0  | 110  | 1.7865          | 17.2554 | 7.4135 | 10.5322 | 10.5689   |
| 1.8066        | 12.0  | 120  | 1.7520          | 15.8483 | 7.1825 | 10.7059 | 10.7344   |
| 1.7476        | 13.0  | 130  | 1.7341          | 16.0049 | 6.6876 | 10.9744 | 10.9918   |
| 1.6911        | 14.0  | 140  | 1.7126          | 17.6921 | 8.9076 | 12.8474 | 12.8966   |
| 1.6388        | 15.0  | 150  | 1.6960          | 19.7192 | 9.1168 | 13.3649 | 13.3949   |
| 1.5902        | 16.0  | 160  | 1.6783          | 20.7583 | 9.7459 | 14.1533 | 14.1794   |
| 1.5433        | 17.0  | 170  | 1.6476          | 19.4203 | 9.4624 | 13.3403 | 13.401    |
| 1.4992        | 18.0  | 180  | 1.6450          | 18.74   | 8.8791 | 13.3925 | 13.3709   |
| 1.4614        | 19.0  | 190  | 1.6335          | 19.476  | 9.0282 | 13.5223 | 13.4966   |
| 1.4216        | 20.0  | 200  | 1.6246          | 17.6435 | 7.9777 | 13.1255 | 13.1599   |
| 1.3842        | 21.0  | 210  | 1.6102          | 18.6282 | 8.511  | 12.8825 | 12.7954   |
| 1.3479        | 22.0  | 220  | 1.6200          | 18.066  | 8.4414 | 12.467  | 12.4232   |
| 1.3087        | 23.0  | 230  | 1.6350          | 17.8312 | 8.6603 | 12.522  | 12.511    |
| 1.2752        | 24.0  | 240  | 1.6186          | 18.5374 | 9.7206 | 13.0955 | 13.0266   |
| 1.2434        | 25.0  | 250  | 1.6219          | 18.232  | 7.9904 | 12.7029 | 12.6916   |
| 1.2046        | 26.0  | 260  | 1.6393          | 17.4585 | 7.2075 | 12.5202 | 12.4766   |
| 1.1716        | 27.0  | 270  | 1.6139          | 19.6477 | 9.9919 | 14.3408 | 14.346    |
| 1.1388        | 28.0  | 280  | 1.6416          | 19.7279 | 8.8207 | 13.6708 | 13.7072   |
| 1.1083        | 29.0  | 290  | 1.6485          | 19.1252 | 9.2133 | 13.6003 | 13.6412   |
| 1.0745        | 30.0  | 300  | 1.6801          | 20.0364 | 9.57   | 13.9743 | 14.0563   |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1