---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
datasets:
- mlsum
metrics:
- rouge
model-index:
- name: t5-small-mlsum
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: mlsum
      type: mlsum
      config: tu
      split: None
      args: tu
    metrics:
    - name: Rouge1
      type: rouge
      value: 14.4732
---

<!-- 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-mlsum

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the mlsum dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6372
- Rouge1: 14.4732
- Rouge2: 6.6752
- Rougel: 13.4183
- Rougelsum: 13.8427
- 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: 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| No log        | 1.0   | 13   | 2.7607          | 14.4395 | 6.4679 | 13.2562 | 13.6373   | 19.0    |
| No log        | 2.0   | 26   | 2.7068          | 14.4214 | 6.4106 | 13.4536 | 13.7502   | 19.0    |
| No log        | 3.0   | 39   | 2.6689          | 14.7941 | 6.5511 | 13.6862 | 14.1839   | 19.0    |
| No log        | 4.0   | 52   | 2.6450          | 14.3539 | 6.6061 | 13.281  | 13.7636   | 19.0    |
| No log        | 5.0   | 65   | 2.6372          | 14.4732 | 6.6752 | 13.4183 | 13.8427   | 19.0    |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1