transformers tensorboard safetensors t5 text2text-generation generated_from_trainer 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
tags:
- generated_from_trainer
model-index:
- name: t5-small_readme_summarization
  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_readme_summarization

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2745
- Rouge1: 0.4187
- Rouge2: 0.2851
- Rougel: 0.3962
- Rougelsum: 0.3961
- Gen Len: 14.4964

## 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: 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.6771        | 1.0   | 1458 | 2.3971          | 0.389  | 0.2544 | 0.3675 | 0.3667    | 14.723  |
| 2.5887        | 2.0   | 2916 | 2.3279          | 0.3967 | 0.2645 | 0.3744 | 0.3752    | 14.4664 |
| 2.4793        | 3.0   | 4374 | 2.2969          | 0.4124 | 0.2786 | 0.3896 | 0.3905    | 14.5564 |
| 2.4421        | 4.0   | 5832 | 2.2758          | 0.4148 | 0.2804 | 0.3923 | 0.3924    | 14.3993 |
| 2.3985        | 5.0   | 7290 | 2.2745          | 0.4187 | 0.2851 | 0.3962 | 0.3961    | 14.4964 |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
