---
license: apache-2.0
tags:
- summarization
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
model-index:
- name: t5-base-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: 48.9131
---

<!-- 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-base-samsum

This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6172
- Rouge1: 48.9131
- Rouge2: 25.4942
- Rougel: 41.2363
- Rougelsum: 45.3434

## 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: 4
- eval_batch_size: 4
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 0.7606        | 1.0   | 3683  | 0.6254          | 46.9778 | 23.8245 | 39.8294 | 43.4639   |
| 0.6273        | 2.0   | 7366  | 0.6119          | 48.2515 | 24.7534 | 40.4415 | 44.5567   |
| 0.5769        | 3.0   | 11049 | 0.6116          | 48.228  | 24.7865 | 40.7537 | 44.4026   |
| 0.5412        | 4.0   | 14732 | 0.6145          | 48.8563 | 25.356  | 41.1913 | 45.186    |
| 0.5199        | 5.0   | 18415 | 0.6172          | 48.9131 | 25.4942 | 41.2363 | 45.3434   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3