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---
base_model: malmarjeh/t5-arabic-text-summarization
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: results
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. -->
# results
This model is a fine-tuned version of [malmarjeh/t5-arabic-text-summarization](https://huggingface.co/malmarjeh/t5-arabic-text-summarization) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0104
- Rouge1: 0.1382
- Rouge2: 0.0187
- Rougel: 0.1382
- Rougelsum: 0.1382
- Gen Len: 18.9404
## 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: 0.0005
- 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
- lr_scheduler_warmup_steps: 100
- num_epochs: 5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 0.0338 | 0.23 | 500 | 0.0175 | 0.1514 | 0.0297 | 0.1511 | 0.1518 | 18.9188 |
| 0.0566 | 0.46 | 1000 | 0.0161 | 0.1565 | 0.0388 | 0.157 | 0.1573 | 18.9188 |
| 0.0418 | 0.7 | 1500 | 0.0125 | 0.1372 | 0.0199 | 0.1375 | 0.1379 | 18.8105 |
| 0.0333 | 0.93 | 2000 | 0.0116 | 0.1443 | 0.0253 | 0.1448 | 0.1448 | 18.8051 |
| 0.0287 | 1.16 | 2500 | 0.0110 | 0.144 | 0.0192 | 0.1442 | 0.1442 | 19.0 |
| 0.0247 | 1.39 | 3000 | 0.0096 | 0.1511 | 0.024 | 0.1517 | 0.1518 | 19.0 |
| 0.0219 | 1.62 | 3500 | 0.0087 | 0.1463 | 0.0241 | 0.1462 | 0.1462 | 18.9747 |
| 0.021 | 1.86 | 4000 | 0.0104 | 0.1382 | 0.0187 | 0.1382 | 0.1382 | 18.9404 |
### Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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