---
base_model: silmi224/finetune-led-35000
tags:
- generated_from_trainer
model-index:
- name: led-risalah-v5
  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-v5

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: 1.5242
- Rouge1 Precision: 0.676
- Rouge1 Recall: 0.1721
- Rouge1 Fmeasure: 0.2728

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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 Precision | Rouge1 Recall | Rouge1 Fmeasure |
|:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
| No log        | 1.0   | 70   | 1.6479          | 0.6178           | 0.1618        | 0.2556          |
| 1.8512        | 2.0   | 140  | 1.5744          | 0.6561           | 0.174         | 0.2745          |
| 1.4296        | 3.0   | 210  | 1.5595          | 0.6617           | 0.1704        | 0.2702          |
| 1.4296        | 4.0   | 280  | 1.5402          | 0.685            | 0.1719        | 0.274           |
| 1.1976        | 5.0   | 350  | 1.5242          | 0.676            | 0.1721        | 0.2728          |
| 1.0638        | 6.0   | 420  | 1.5383          | 0.6886           | 0.182         | 0.2873          |
| 1.0638        | 7.0   | 490  | 1.5652          | 0.6636           | 0.1757        | 0.2771          |
| 0.9657        | 8.0   | 560  | 1.5797          | 0.6788           | 0.172         | 0.2733          |
| 0.9215        | 9.0   | 630  | 1.5960          | 0.6644           | 0.1715        | 0.2715          |
| 0.849         | 10.0  | 700  | 1.5943          | 0.6581           | 0.1693        | 0.2681          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.15.1