---
base_model: weny22/sum_model_t5_saved
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: extract_long_text_unbalanced_smaller
  results: []
---

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

This model is a fine-tuned version of [weny22/sum_model_t5_saved](https://huggingface.co/weny22/sum_model_t5_saved) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4822
- Rouge1: 0.1997
- Rouge2: 0.0696
- Rougel: 0.1604
- Rougelsum: 0.1602
- Gen Len: 18.9893

## 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: 0.002
- train_batch_size: 64
- eval_batch_size: 64
- 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 | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 72   | 2.6068          | 0.1714 | 0.0484 | 0.1369 | 0.1367    | 18.988  |
| No log        | 2.0   | 144  | 2.3827          | 0.1801 | 0.0547 | 0.1414 | 0.1412    | 18.994  |
| No log        | 3.0   | 216  | 2.2953          | 0.1858 | 0.0568 | 0.1457 | 0.1456    | 19.0    |
| No log        | 4.0   | 288  | 2.2509          | 0.188  | 0.0599 | 0.1479 | 0.1478    | 18.9953 |
| No log        | 5.0   | 360  | 2.2338          | 0.1834 | 0.057  | 0.1449 | 0.1447    | 18.9967 |
| No log        | 6.0   | 432  | 2.2428          | 0.1871 | 0.0608 | 0.1483 | 0.1482    | 18.9953 |
| 3.0458        | 7.0   | 504  | 2.2195          | 0.1926 | 0.0626 | 0.1538 | 0.1537    | 18.9867 |
| 3.0458        | 8.0   | 576  | 2.2549          | 0.1932 | 0.0619 | 0.1521 | 0.152     | 18.9967 |
| 3.0458        | 9.0   | 648  | 2.2675          | 0.1955 | 0.0642 | 0.156  | 0.1558    | 18.9607 |
| 3.0458        | 10.0  | 720  | 2.2858          | 0.1981 | 0.0665 | 0.1573 | 0.1572    | 18.9807 |
| 3.0458        | 11.0  | 792  | 2.2980          | 0.1942 | 0.0653 | 0.1557 | 0.1554    | 18.972  |
| 3.0458        | 12.0  | 864  | 2.3413          | 0.1999 | 0.0682 | 0.1597 | 0.1595    | 18.9807 |
| 3.0458        | 13.0  | 936  | 2.3324          | 0.1987 | 0.0676 | 0.1585 | 0.1585    | 18.9733 |
| 1.907         | 14.0  | 1008 | 2.3481          | 0.2002 | 0.0688 | 0.1599 | 0.1597    | 18.9913 |
| 1.907         | 15.0  | 1080 | 2.4027          | 0.2023 | 0.0704 | 0.1617 | 0.1617    | 18.9887 |
| 1.907         | 16.0  | 1152 | 2.4132          | 0.2032 | 0.0728 | 0.1634 | 0.1634    | 18.9833 |
| 1.907         | 17.0  | 1224 | 2.4393          | 0.1988 | 0.0682 | 0.1586 | 0.1584    | 18.9853 |
| 1.907         | 18.0  | 1296 | 2.4435          | 0.1991 | 0.0698 | 0.1594 | 0.1591    | 18.9867 |
| 1.907         | 19.0  | 1368 | 2.4703          | 0.2014 | 0.0703 | 0.1608 | 0.1608    | 18.9873 |
| 1.907         | 20.0  | 1440 | 2.4822          | 0.1997 | 0.0696 | 0.1604 | 0.1602    | 18.9893 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2