---
license: apache-2.0
tags:
- summarization
- generated_from_trainer
model-index:
- name: t5-small-salidaLarga-tfg
  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-salidaLarga-tfg

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: 3.3428
- Rouge2 Precision: 0.0633
- Rouge2 Recall: 0.1234
- Rouge2 Fmeasure: 0.0835

## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
| 7.2339        | 0.27  | 10   | 4.7620          | 0.0337           | 0.0321        | 0.0327          |
| 4.3192        | 0.53  | 20   | 4.0073          | 0.0427           | 0.05          | 0.046           |
| 3.9608        | 0.8   | 30   | 3.6537          | 0.0589           | 0.0922        | 0.0717          |
| 3.7992        | 1.07  | 40   | 3.4747          | 0.0626           | 0.1114        | 0.08            |
| 3.7694        | 1.33  | 50   | 3.3968          | 0.0618           | 0.1145        | 0.0801          |
| 3.5839        | 1.6   | 60   | 3.3600          | 0.0654           | 0.1248        | 0.0856          |
| 3.5573        | 1.87  | 70   | 3.3428          | 0.0633           | 0.1234        | 0.0835          |


### Framework versions

- Transformers 4.27.4
- Pytorch 1.13.1+cu116
- Datasets 2.11.0
- Tokenizers 0.13.2