---
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