---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-summ
  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. -->

# t5-summ

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0871
- Rouge1: 0.1961
- Rouge2: 0.099
- Rougel: 0.1691
- Rougelsum: 0.1691
- 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 62   | 2.6868          | 0.1256 | 0.0388 | 0.1039 | 0.104     | 19.0    |
| No log        | 2.0   | 124  | 2.4594          | 0.143  | 0.0547 | 0.1191 | 0.1193    | 19.0    |
| No log        | 3.0   | 186  | 2.3653          | 0.1677 | 0.0718 | 0.1396 | 0.1396    | 19.0    |
| No log        | 4.0   | 248  | 2.3113          | 0.1913 | 0.0917 | 0.1613 | 0.161     | 19.0    |
| No log        | 5.0   | 310  | 2.2735          | 0.196  | 0.0974 | 0.1665 | 0.1663    | 19.0    |
| No log        | 6.0   | 372  | 2.2417          | 0.1972 | 0.0996 | 0.1687 | 0.1686    | 19.0    |
| No log        | 7.0   | 434  | 2.2197          | 0.1985 | 0.1011 | 0.17   | 0.1699    | 19.0    |
| No log        | 8.0   | 496  | 2.2011          | 0.1982 | 0.1012 | 0.1698 | 0.1697    | 19.0    |
| 2.7383        | 9.0   | 558  | 2.1829          | 0.198  | 0.1    | 0.1698 | 0.1698    | 19.0    |
| 2.7383        | 10.0  | 620  | 2.1724          | 0.1985 | 0.1011 | 0.1703 | 0.1702    | 19.0    |
| 2.7383        | 11.0  | 682  | 2.1605          | 0.1991 | 0.1017 | 0.1708 | 0.1709    | 19.0    |
| 2.7383        | 12.0  | 744  | 2.1489          | 0.1992 | 0.1022 | 0.1717 | 0.1719    | 19.0    |
| 2.7383        | 13.0  | 806  | 2.1420          | 0.1994 | 0.1028 | 0.1716 | 0.1716    | 19.0    |
| 2.7383        | 14.0  | 868  | 2.1322          | 0.2003 | 0.1041 | 0.1726 | 0.1726    | 19.0    |
| 2.7383        | 15.0  | 930  | 2.1265          | 0.2    | 0.103  | 0.172  | 0.1719    | 19.0    |
| 2.7383        | 16.0  | 992  | 2.1196          | 0.1993 | 0.1014 | 0.1718 | 0.1718    | 19.0    |
| 2.3748        | 17.0  | 1054 | 2.1165          | 0.1979 | 0.1011 | 0.1709 | 0.1709    | 19.0    |
| 2.3748        | 18.0  | 1116 | 2.1090          | 0.1985 | 0.1011 | 0.1701 | 0.1703    | 19.0    |
| 2.3748        | 19.0  | 1178 | 2.1063          | 0.1984 | 0.1014 | 0.1706 | 0.1708    | 19.0    |
| 2.3748        | 20.0  | 1240 | 2.1031          | 0.1993 | 0.1031 | 0.1714 | 0.1715    | 19.0    |
| 2.3748        | 21.0  | 1302 | 2.0997          | 0.1982 | 0.1018 | 0.1707 | 0.1708    | 19.0    |
| 2.3748        | 22.0  | 1364 | 2.0970          | 0.1966 | 0.1002 | 0.1692 | 0.1694    | 19.0    |
| 2.3748        | 23.0  | 1426 | 2.0951          | 0.1948 | 0.0986 | 0.1681 | 0.1682    | 19.0    |
| 2.3748        | 24.0  | 1488 | 2.0928          | 0.1959 | 0.0995 | 0.1691 | 0.1693    | 19.0    |
| 2.2969        | 25.0  | 1550 | 2.0919          | 0.1958 | 0.0995 | 0.1689 | 0.169     | 19.0    |
| 2.2969        | 26.0  | 1612 | 2.0892          | 0.1955 | 0.099  | 0.1687 | 0.1688    | 19.0    |
| 2.2969        | 27.0  | 1674 | 2.0883          | 0.196  | 0.0994 | 0.1692 | 0.1692    | 19.0    |
| 2.2969        | 28.0  | 1736 | 2.0877          | 0.1959 | 0.0994 | 0.1692 | 0.1693    | 19.0    |
| 2.2969        | 29.0  | 1798 | 2.0871          | 0.196  | 0.0995 | 0.1692 | 0.1692    | 19.0    |
| 2.2969        | 30.0  | 1860 | 2.0871          | 0.1961 | 0.099  | 0.1691 | 0.1691    | 19.0    |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2