---
base_model: UBC-NLP/AraT5v2-base-1024
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: results_arat5-2_wiki
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# results_arat5-2_wiki

This model is a fine-tuned version of [UBC-NLP/AraT5v2-base-1024](https://huggingface.co/UBC-NLP/AraT5v2-base-1024) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 5.6421
- Rouge1: 0.0905
- Rouge2: 0.0
- Rougel: 0.0915
- Rougelsum: 0.0912
- Gen Len: 19.0

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 8.3962        | 0.9506 | 500  | 7.0927          | 0.0    | 0.0    | 0.0    | 0.0       | 0.0     |
| 7.072         | 1.9011 | 1000 | 7.0704          | 0.0    | 0.0    | 0.0    | 0.0       | 0.0     |
| 7.0441        | 2.8517 | 1500 | 7.0627          | 0.0    | 0.0    | 0.0    | 0.0       | 0.0     |
| 7.0044        | 3.8023 | 2000 | 7.0205          | 0.0    | 0.0    | 0.0    | 0.0       | 16.9719 |
| 6.9461        | 4.7529 | 2500 | 6.8398          | 0.0896 | 0.0    | 0.0908 | 0.0904    | 17.7903 |
| 6.727         | 5.7034 | 3000 | 6.5676          | 0.0905 | 0.0    | 0.0915 | 0.0912    | 18.8221 |
| 6.446         | 6.6540 | 3500 | 6.3711          | 0.0905 | 0.0    | 0.0915 | 0.0912    | 18.8221 |
| 6.3054        | 7.6046 | 4000 | 5.9586          | 0.0905 | 0.0    | 0.0915 | 0.0912    | 18.8933 |
| 5.8985        | 8.5551 | 4500 | 5.7386          | 0.0905 | 0.0    | 0.0915 | 0.0912    | 19.0    |
| 5.8333        | 9.5057 | 5000 | 5.6421          | 0.0905 | 0.0    | 0.0915 | 0.0912    | 19.0    |


### Framework versions

- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1