---
base_model: weny22/sum_model_t5_saved
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: extract_long_text_unbalanced_smaller_5
  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. -->

# extract_long_text_unbalanced_smaller_5

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: 2.2242
- Rouge1: 0.2008
- Rouge2: 0.0688
- Rougel: 0.1593
- Rougelsum: 0.1594
- Gen Len: 18.9847

## 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: 0.001
- 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   | 2.3970          | 0.1842 | 0.0572 | 0.1461 | 0.1458    | 18.98   |
| No log        | 2.0   | 144  | 2.2826          | 0.1923 | 0.0623 | 0.1516 | 0.1515    | 19.0    |
| No log        | 3.0   | 216  | 2.2308          | 0.1945 | 0.0634 | 0.1529 | 0.1527    | 18.9953 |
| No log        | 4.0   | 288  | 2.1962          | 0.1944 | 0.0636 | 0.1528 | 0.1527    | 18.9967 |
| No log        | 5.0   | 360  | 2.1940          | 0.1948 | 0.0633 | 0.1529 | 0.1528    | 18.9953 |
| No log        | 6.0   | 432  | 2.1734          | 0.1882 | 0.0628 | 0.1492 | 0.1491    | 18.99   |
| 3.0387        | 7.0   | 504  | 2.1584          | 0.1964 | 0.0663 | 0.156  | 0.1559    | 18.992  |
| 3.0387        | 8.0   | 576  | 2.1588          | 0.197  | 0.068  | 0.1563 | 0.1562    | 18.9847 |
| 3.0387        | 9.0   | 648  | 2.1852          | 0.1967 | 0.0669 | 0.156  | 0.1559    | 18.9793 |
| 3.0387        | 10.0  | 720  | 2.1859          | 0.201  | 0.0685 | 0.159  | 0.1587    | 18.982  |
| 3.0387        | 11.0  | 792  | 2.1760          | 0.1936 | 0.0643 | 0.1534 | 0.1531    | 18.9953 |
| 3.0387        | 12.0  | 864  | 2.2081          | 0.1978 | 0.0672 | 0.1566 | 0.1564    | 18.9753 |
| 3.0387        | 13.0  | 936  | 2.2030          | 0.1991 | 0.068  | 0.1584 | 0.158     | 18.9833 |
| 2.204         | 14.0  | 1008 | 2.2029          | 0.1981 | 0.0686 | 0.1578 | 0.1578    | 18.9867 |
| 2.204         | 15.0  | 1080 | 2.2076          | 0.2016 | 0.0694 | 0.1595 | 0.1592    | 18.9773 |
| 2.204         | 16.0  | 1152 | 2.2172          | 0.203  | 0.0716 | 0.1617 | 0.1617    | 18.9893 |
| 2.204         | 17.0  | 1224 | 2.2136          | 0.2018 | 0.0697 | 0.1604 | 0.1603    | 18.9827 |
| 2.204         | 18.0  | 1296 | 2.2147          | 0.2016 | 0.0695 | 0.1601 | 0.1599    | 18.988  |
| 2.204         | 19.0  | 1368 | 2.2224          | 0.2007 | 0.0687 | 0.1592 | 0.1592    | 18.9847 |
| 2.204         | 20.0  | 1440 | 2.2242          | 0.2008 | 0.0688 | 0.1593 | 0.1594    | 18.9847 |


### Framework versions

- Transformers 4.39.1
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2