---
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
model-index:
- name: t5-finetuned-summarization-samsum
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: samsum
      type: samsum
      config: samsum
      split: validation
      args: samsum
    metrics:
    - name: Rouge1
      type: rouge
      value: 43.6894
---

<!-- 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-finetuned-summarization-samsum

This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6551
- Rouge1: 43.6894
- Rouge2: 21.0711
- Rougel: 36.7865
- Rougelsum: 40.2927

## 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: 5e-05
- 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: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 2.0612        | 1.0   | 1842  | 1.7709          | 40.7189 | 17.9391 | 34.0848 | 37.86     |
| 1.8988        | 2.0   | 3684  | 1.7278          | 41.1985 | 18.7817 | 34.8297 | 38.378    |
| 1.8283        | 3.0   | 5526  | 1.6946          | 42.5298 | 19.6906 | 35.7159 | 39.2425   |
| 1.7798        | 4.0   | 7368  | 1.6860          | 42.9966 | 20.7335 | 36.5141 | 39.7994   |
| 1.7418        | 5.0   | 9210  | 1.6677          | 42.8533 | 20.4738 | 36.1407 | 39.5548   |
| 1.7157        | 6.0   | 11052 | 1.6645          | 43.6738 | 21.055  | 36.8091 | 40.3053   |
| 1.6896        | 7.0   | 12894 | 1.6584          | 43.5629 | 20.8972 | 36.614  | 40.2316   |
| 1.6756        | 8.0   | 14736 | 1.6567          | 43.8709 | 21.4421 | 36.9208 | 40.5036   |
| 1.6624        | 9.0   | 16578 | 1.6568          | 43.6278 | 21.0048 | 36.668  | 40.2666   |
| 1.6558        | 10.0  | 18420 | 1.6551          | 43.6894 | 21.0711 | 36.7865 | 40.2927   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1