---
base_model: aubmindlab/aragpt2-base
tags:
- generated_from_trainer
metrics:
- bleu
- rouge
model-index:
- name: res_nw_yem_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_yem_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: 0.0534
- Bleu: 0.0428
- Rouge1: 0.3139
- Rouge2: 0.1104
- Rougel: 0.3097

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:------:|
| 5.8224        | 1.0   | 153  | 0.1129          | 0.0039 | 0.0712 | 0.0029 | 0.0695 |
| 0.1108        | 2.0   | 306  | 0.0691          | 0.0    | 0.0951 | 0.0078 | 0.0932 |
| 0.0775        | 3.0   | 459  | 0.0628          | 0.0067 | 0.1291 | 0.0157 | 0.1286 |
| 0.0678        | 4.0   | 612  | 0.0592          | 0.0086 | 0.1524 | 0.0273 | 0.1492 |
| 0.0603        | 5.0   | 765  | 0.0566          | 0.0162 | 0.1919 | 0.0413 | 0.1883 |
| 0.0547        | 6.0   | 918  | 0.0546          | 0.0187 | 0.2239 | 0.0599 | 0.2218 |
| 0.0498        | 7.0   | 1071 | 0.0540          | 0.0295 | 0.2684 | 0.0733 | 0.2638 |
| 0.0456        | 8.0   | 1224 | 0.0536          | 0.0292 | 0.2884 | 0.0818 | 0.2841 |
| 0.0419        | 9.0   | 1377 | 0.0534          | 0.0428 | 0.3139 | 0.1104 | 0.3097 |
| 0.0385        | 10.0  | 1530 | 0.0534          | 0.0461 | 0.3255 | 0.1118 | 0.3185 |
| 0.0354        | 11.0  | 1683 | 0.0540          | 0.0473 | 0.3358 | 0.1219 | 0.3288 |
| 0.0331        | 12.0  | 1836 | 0.0540          | 0.0476 | 0.3483 | 0.1312 | 0.3442 |
| 0.0308        | 13.0  | 1989 | 0.0552          | 0.0590 | 0.3599 | 0.1439 | 0.3539 |
| 0.0291        | 14.0  | 2142 | 0.0556          | 0.0625 | 0.3737 | 0.1489 | 0.3670 |


### Framework versions

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