---
base_model: aubmindlab/aragpt2-base
tags:
- generated_from_trainer
metrics:
- bleu
- rouge
model-index:
- name: res_nw_dj_aragpt2-base
  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. -->

# res_nw_dj_aragpt2-base

This model is a fine-tuned version of [aubmindlab/aragpt2-base](https://huggingface.co/aubmindlab/aragpt2-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0752
- Bleu: 0.0928
- Rouge1: 0.4343
- Rouge2: 0.2043
- Rougel: 0.4304

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 20.0

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu   | Rouge1 | Rouge2 | Rougel |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:------:|
| 0.435         | 1.0   | 2679  | 0.0899          | 0.0225 | 0.2697 | 0.0681 | 0.2649 |
| 0.0908        | 2.0   | 5358  | 0.0822          | 0.0495 | 0.3438 | 0.1233 | 0.3394 |
| 0.0808        | 3.0   | 8037  | 0.0786          | 0.0670 | 0.3835 | 0.1582 | 0.3790 |
| 0.0738        | 4.0   | 10716 | 0.0765          | 0.0782 | 0.4066 | 0.1798 | 0.4025 |
| 0.0681        | 5.0   | 13395 | 0.0756          | 0.0880 | 0.4242 | 0.1964 | 0.4204 |
| 0.0632        | 6.0   | 16074 | 0.0752          | 0.0928 | 0.4343 | 0.2043 | 0.4304 |
| 0.059         | 7.0   | 18753 | 0.0755          | 0.0996 | 0.4439 | 0.2152 | 0.4401 |
| 0.0552        | 8.0   | 21432 | 0.0761          | 0.1015 | 0.4500 | 0.2217 | 0.4463 |
| 0.0517        | 9.0   | 24111 | 0.0766          | 0.1050 | 0.4527 | 0.2250 | 0.4489 |
| 0.0486        | 10.0  | 26790 | 0.0784          | 0.1093 | 0.4612 | 0.2338 | 0.4578 |
| 0.0458        | 11.0  | 29469 | 0.0798          | 0.1112 | 0.4634 | 0.2356 | 0.4600 |


### Framework versions

- Transformers 4.45.0.dev0
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1