---
base_model: aubmindlab/aragpt2-base
tags:
- generated_from_trainer
metrics:
- bleu
- rouge
model-index:
- name: res_nw_eg_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_eg_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: 0.1032
- Bleu: 0.1405
- Rouge1: 0.4455
- Rouge2: 0.2251
- Rougel: 0.4383

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:------:|
| 0.2542        | 1.0   | 7105  | 0.1199          | 0.0729 | 0.3187 | 0.1103 | 0.3094 |
| 0.1078        | 2.0   | 14210 | 0.1119          | 0.1044 | 0.3803 | 0.1636 | 0.3720 |
| 0.0972        | 3.0   | 21315 | 0.1077          | 0.1222 | 0.4109 | 0.1933 | 0.4033 |
| 0.0902        | 4.0   | 28420 | 0.1051          | 0.1312 | 0.4294 | 0.2090 | 0.4223 |
| 0.0846        | 5.0   | 35525 | 0.1032          | 0.1405 | 0.4455 | 0.2251 | 0.4383 |
| 0.0799        | 6.0   | 42630 | 0.1041          | 0.1454 | 0.4537 | 0.2338 | 0.4466 |
| 0.0759        | 7.0   | 49735 | 0.1044          | 0.1494 | 0.4623 | 0.2425 | 0.4553 |
| 0.0722        | 8.0   | 56840 | 0.1044          | 0.1527 | 0.4655 | 0.2470 | 0.4587 |
| 0.069         | 9.0   | 63945 | 0.1058          | 0.1536 | 0.4689 | 0.2489 | 0.4621 |
| 0.066         | 10.0  | 71050 | 0.1062          | 0.1550 | 0.4724 | 0.2523 | 0.4657 |


### Framework versions

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