---
tags:
- summarization
- generated_from_trainer
model-index:
- name: led-risalah_data_v13
  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_v13

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5198
- Rouge1 Precision: 0.4184
- Rouge1 Recall: 0.4032
- Rouge1 Fmeasure: 0.4092

## 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: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rouge1 Fmeasure | Rouge1 Precision | Rouge1 Recall |
|:-------------:|:------:|:----:|:---------------:|:---------------:|:----------------:|:-------------:|
| 3.1517        | 0.9714 | 17   | 2.3560          | 0.2698          | 0.277            | 0.2642        |
| 2.2618        | 2.0    | 35   | 2.1487          | 0.3183          | 0.3295           | 0.3091        |
| 1.9714        | 2.9714 | 52   | 2.0826          | 0.3383          | 0.358            | 0.3226        |
| 1.8991        | 4.0    | 70   | 2.0284          | 0.34            | 0.3579           | 0.3248        |
| 1.7713        | 4.9714 | 87   | 1.9871          | 0.3667          | 0.3744           | 0.3602        |
| 1.7889        | 6.0    | 105  | 1.9714          | 0.3614          | 0.3729           | 0.3521        |
| 1.6378        | 6.9714 | 122  | 1.9481          | 0.3589          | 0.3762           | 0.3461        |
| 1.5649        | 8.0    | 140  | 1.9426          | 0.3657          | 0.3802           | 0.3545        |
| 1.5157        | 8.9714 | 157  | 1.9349          | 0.3667          | 0.375            | 0.361         |


### Framework versions

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