---
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: finetuned_t5_summarize
  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. -->

# finetuned_t5_summarize

This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2034
- Rouge1: 0.8046
- Rouge2: 0.7768
- Rougel: 0.8018
- Rougelsum: 0.8018
- Gen Len: 16.8404

## 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: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 301  | 0.2652          | 0.7765 | 0.7432 | 0.7726 | 0.7728    | 16.7722 |
| 0.3923        | 2.0   | 602  | 0.2248          | 0.7967 | 0.768  | 0.7944 | 0.7943    | 16.7797 |
| 0.3923        | 3.0   | 903  | 0.2074          | 0.8027 | 0.775  | 0.7997 | 0.7996    | 16.8105 |
| 0.2356        | 4.0   | 1204 | 0.2034          | 0.8046 | 0.7768 | 0.8018 | 0.8018    | 16.8404 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2