---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: summarization_model
  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. -->

# summarization_model

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1359
- Rouge1: 0.1813
- Rouge2: 0.1114
- Rougel: 0.1616
- Rougelsum: 0.1617
- 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: 8
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 0.2358        | 1.0   | 1635  | 0.1719          | 0.1758 | 0.1033 | 0.1554 | 0.1554    | 19.0    |
| 0.2043        | 2.0   | 3270  | 0.1574          | 0.1764 | 0.1046 | 0.1561 | 0.1561    | 19.0    |
| 0.191         | 3.0   | 4905  | 0.1505          | 0.1778 | 0.1069 | 0.1577 | 0.1578    | 19.0    |
| 0.178         | 4.0   | 6540  | 0.1448          | 0.1797 | 0.1093 | 0.1597 | 0.1597    | 19.0    |
| 0.1734        | 5.0   | 8175  | 0.1406          | 0.1804 | 0.1102 | 0.1605 | 0.1604    | 19.0    |
| 0.1681        | 6.0   | 9810  | 0.1376          | 0.1811 | 0.111  | 0.1613 | 0.1613    | 19.0    |
| 0.1665        | 7.0   | 11445 | 0.1365          | 0.1815 | 0.1114 | 0.1618 | 0.1618    | 19.0    |
| 0.1643        | 8.0   | 13080 | 0.1359          | 0.1813 | 0.1114 | 0.1616 | 0.1617    | 19.0    |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3