---
library_name: transformers
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
model-index:
- name: t5_small_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: 0.4282
---

<!-- 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_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: 1.7255
- Rouge1: 0.4282
- Rouge2: 0.2003
- Rougel: 0.36
- Rougelsum: 0.3596
- Gen Len: 16.7372

## 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: 3e-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: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 1.9452        | 1.0   | 921  | 1.7726          | 0.4147 | 0.1901 | 0.3492 | 0.3493    | 16.4719 |
| 1.8952        | 2.0   | 1842 | 1.7498          | 0.4237 | 0.1971 | 0.3577 | 0.3577    | 16.4548 |
| 1.8703        | 3.0   | 2763 | 1.7323          | 0.4243 | 0.1968 | 0.3571 | 0.3566    | 16.7689 |
| 1.8579        | 4.0   | 3684 | 1.7310          | 0.4262 | 0.2012 | 0.3606 | 0.3604    | 16.7641 |
| 1.8525        | 5.0   | 4605 | 1.7255          | 0.4282 | 0.2003 | 0.36   | 0.3596    | 16.7372 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1