transformers tensorboard safetensors t5 text2text-generation generated_from_trainer summarization base_model:google-t5/t5-small base_model:finetune:google-t5/t5-small license:apache-2.0 autotrain_compatible text-generation-inference endpoints_compatible region:us
---
base_model: t5-small
license: apache-2.0
metrics:
- rouge
pipeline_tag: summarization
tags:
- generated_from_trainer
model-index:
- name: t5-small-finetuned-samsum
  results: []
---

<!-- 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-finetuned-samsum

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7651
- Rouge1: 41.6124
- Rouge2: 18.7668
- Rougel: 35.0271
- Rougelsum: 38.5305
- Gen Len: 16.6381

## 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: 2e-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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.044         | 1.0   | 921  | 1.8159          | 41.1358 | 18.1022 | 34.3309 | 38.1969   | 16.5232 |
| 1.9796        | 2.0   | 1842 | 1.7915          | 41.4713 | 18.6313 | 34.7999 | 38.4147   | 16.566  |
| 1.9487        | 3.0   | 2763 | 1.7724          | 41.6106 | 18.6119 | 34.7796 | 38.5737   | 16.7213 |
| 1.9265        | 4.0   | 3684 | 1.7687          | 41.6027 | 18.8083 | 34.8846 | 38.566    | 16.676  |
| 1.9176        | 5.0   | 4605 | 1.7651          | 41.6124 | 18.7668 | 35.0271 | 38.5305   | 16.6381 |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1