---
base_model: hiba2/results_arat5-2_wiki
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: results_arat5-3_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_arat5-3_wiki

This model is a fine-tuned version of [hiba2/results_arat5-2_wiki](https://huggingface.co/hiba2/results_arat5-2_wiki) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7821
- Rouge1: 0.0926
- Rouge2: 0.0015
- Rougel: 0.0934
- Rougelsum: 0.0928
- 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: 20

### Training results

| Training Loss | Epoch   | Step  | Gen Len | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-------:|:-----:|:-------:|:---------------:|:------:|:------:|:------:|:---------:|
| 7.8936        | 0.9506  | 500   | 0.0     | 5.9107          | 0.0    | 0.0    | 0.0    | 0.0       |
| 5.5649        | 1.9011  | 1000  | 18.8876 | 4.9336          | 0.0905 | 0.0    | 0.0915 | 0.0912    |
| 4.9098        | 2.8517  | 1500  | 18.8989 | 4.3731          | 0.0905 | 0.0    | 0.0915 | 0.0912    |
| 4.4486        | 3.8023  | 2000  | 19.0    | 3.9340          | 0.0875 | 0.0    | 0.0885 | 0.0882    |
| 4.0755        | 4.7529  | 2500  | 18.9382 | 3.5412          | 0.0881 | 0.0    | 0.0891 | 0.0887    |
| 3.6998        | 5.7034  | 3000  | 18.8783 | 3.1344          | 0.095  | 0.0002 | 0.0958 | 0.0954    |
| 3.3129        | 6.6540  | 3500  | 18.8408 | 2.8528          | 0.0935 | 0.0013 | 0.0945 | 0.094     |
| 3.1053        | 7.6046  | 4000  | 18.9382 | 2.6196          | 0.0936 | 0.0008 | 0.0946 | 0.0941    |
| 2.8412        | 8.5551  | 4500  | 18.867  | 2.4414          | 0.091  | 0.0011 | 0.0919 | 0.0915    |
| 2.702         | 9.5057  | 5000  | 18.8783 | 2.2952          | 0.0936 | 0.001  | 0.0948 | 0.0946    |
| 2.5611        | 10.4563 | 5500  | 19.0    | 2.1816          | 0.093  | 0.0011 | 0.0941 | 0.0936    |
| 2.4499        | 11.4068 | 6000  | 18.8502 | 2.0914          | 0.0988 | 0.0011 | 0.0995 | 0.099     |
| 2.3764        | 12.3574 | 6500  | 18.8371 | 2.0264          | 0.0992 | 0.0016 | 0.0997 | 0.0995    |
| 2.3172        | 13.3080 | 7000  | 18.9888 | 1.9853          | 0.098  | 0.0015 | 0.099  | 0.0986    |
| 2.2794        | 14.2586 | 7500  | 18.9888 | 1.9615          | 0.0971 | 0.0023 | 0.0977 | 0.0976    |
| 2.2178        | 15.2091 | 8000  | 1.9424  | 0.0961          | 0.0009 | 0.0972 | 0.0968 | 19.0      |
| 2.2378        | 16.1597 | 8500  | 1.8855  | 0.0935          | 0.0011 | 0.0942 | 0.0937 | 19.0      |
| 2.1573        | 17.1103 | 9000  | 1.8386  | 0.0952          | 0.0009 | 0.0962 | 0.0958 | 19.0      |
| 2.132         | 18.0608 | 9500  | 1.8055  | 0.0919          | 0.0012 | 0.0929 | 0.0923 | 18.8783   |
| 2.1035        | 19.0114 | 10000 | 1.7863  | 0.0942          | 0.0015 | 0.0949 | 0.0945 | 19.0      |
| 2.0818        | 19.9620 | 10500 | 1.7821  | 0.0926          | 0.0015 | 0.0934 | 0.0928 | 19.0      |


### Framework versions

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