---
base_model: UBC-NLP/AraT5v2-base-1024
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: results_arat5_wiki
  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_arat5_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: 2.4401
- 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: 0.0005
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:------:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 7.7921        | 0.4757 | 500   | 6.2870          | 0.0905 | 0.0    | 0.0915 | 0.0912    | 19.0    |
| 5.9839        | 0.9515 | 1000  | 5.5934          | 0.0905 | 0.0    | 0.0915 | 0.0912    | 19.0    |
| 5.4311        | 1.4272 | 1500  | 5.0896          | 0.0905 | 0.0    | 0.0915 | 0.0912    | 19.0    |
| 5.1245        | 1.9029 | 2000  | 4.7004          | 0.0905 | 0.0    | 0.0915 | 0.0912    | 19.0    |
| 4.7258        | 2.3787 | 2500  | 4.3347          | 0.0905 | 0.0    | 0.0915 | 0.0912    | 19.0    |
| 4.5072        | 2.8544 | 3000  | 4.0503          | 0.0905 | 0.0    | 0.0915 | 0.0912    | 19.0    |
| 4.2388        | 3.3302 | 3500  | 3.8321          | 0.0905 | 0.0    | 0.0915 | 0.0912    | 19.0    |
| 4.0817        | 3.8059 | 4000  | 3.6509          | 0.0905 | 0.0    | 0.0915 | 0.0912    | 19.0    |
| 3.8843        | 4.2816 | 4500  | 3.4451          | 0.0905 | 0.0    | 0.0915 | 0.0912    | 19.0    |
| 3.7958        | 4.7574 | 5000  | 3.3071          | 0.0905 | 0.0    | 0.0915 | 0.0912    | 19.0    |
| 3.6397        | 5.2331 | 5500  | 3.1619          | 0.0905 | 0.0    | 0.0915 | 0.0912    | 19.0    |
| 3.5658        | 5.7088 | 6000  | 3.0068          | 0.0905 | 0.0    | 0.0915 | 0.0912    | 19.0    |
| 3.4171        | 6.1846 | 6500  | 2.9459          | 0.0905 | 0.0    | 0.0915 | 0.0912    | 19.0    |
| 3.2697        | 6.6603 | 7000  | 2.8074          | 0.0842 | 0.0    | 0.0849 | 0.0844    | 19.0    |
| 3.3168        | 7.1361 | 7500  | 2.7153          | 0.0905 | 0.0    | 0.0915 | 0.0912    | 19.0    |
| 3.1594        | 7.6118 | 8000  | 2.6676          | 0.0905 | 0.0    | 0.0915 | 0.0912    | 19.0    |
| 3.0928        | 8.0875 | 8500  | 2.5849          | 0.0905 | 0.0    | 0.0915 | 0.0912    | 19.0    |
| 3.0318        | 8.5633 | 9000  | 2.5152          | 0.0905 | 0.0    | 0.0915 | 0.0912    | 19.0    |
| 3.0392        | 9.0390 | 9500  | 2.4849          | 0.0902 | 0.0    | 0.0911 | 0.0908    | 19.0    |
| 2.9917        | 9.5147 | 10000 | 2.4569          | 0.0768 | 0.0001 | 0.0774 | 0.0768    | 19.0    |
| 2.9281        | 9.9905 | 10500 | 2.4401          | 0.0905 | 0.0    | 0.0915 | 0.0912    | 19.0    |


### Framework versions

- Transformers 4.42.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1