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---
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: 0.0798
- Bleu: 0.1112
- Rouge1: 0.4634
- Rouge2: 0.2356
- Rougel: 0.4600
## 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
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