---
library_name: transformers
license: apache-2.0
base_model: t5-small
tags:
- summarization
- generated_from_trainer
datasets:
- multi_news
metrics:
- rouge
model-index:
- name: t5-small-Abstractive-Summarizer
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: multi_news
      type: multi_news
      config: default
      split: validation
      args: default
    metrics:
    - name: Rouge1
      type: rouge
      value: 15.0486
---

<!-- 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-small-Abstractive-Summarizer

This model is a fine-tuned version of [t5-small](https://huggingface.co./t5-small) on the multi_news dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8162
- Rouge1: 15.0486
- Rouge2: 5.1197
- Rougel: 12.0288
- Rougelsum: 13.4434

## 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: 0.00056
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 2.7895        | 1.0   | 113  | 2.7479          | 15.6051 | 5.1347 | 12.2224 | 13.8875   |
| 2.6034        | 2.0   | 226  | 2.7745          | 15.2054 | 4.7334 | 11.7555 | 13.436    |
| 2.4515        | 3.0   | 339  | 2.7820          | 15.008  | 4.6612 | 11.5993 | 13.3788   |
| 2.3439        | 4.0   | 452  | 2.8056          | 15.2475 | 4.9304 | 11.8552 | 13.4615   |
| 2.2803        | 5.0   | 565  | 2.8162          | 15.0486 | 5.1197 | 12.0288 | 13.4434   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1