---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-small-MedicoSummarizer
  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-MedicoSummarizer

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: 2.9737
- Rouge1: 0.3207
- Rouge2: 0.0752
- Rougel: 0.1949
- Rougelsum: 0.1947
- Gen Len: 122.586

## 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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 3.4289        | 1.0   | 625  | 3.0929          | 0.3181 | 0.0722 | 0.1893 | 0.1893    | 122.637 |
| 3.2654        | 2.0   | 1250 | 3.0531          | 0.3199 | 0.0733 | 0.1915 | 0.1916    | 122.072 |
| 3.2288        | 3.0   | 1875 | 3.0245          | 0.317  | 0.0725 | 0.1917 | 0.1917    | 122.153 |
| 3.178         | 4.0   | 2500 | 3.0097          | 0.3161 | 0.0724 | 0.1907 | 0.1907    | 122.398 |
| 3.16          | 5.0   | 3125 | 2.9940          | 0.3162 | 0.0722 | 0.192  | 0.1918    | 122.114 |
| 3.1517        | 6.0   | 3750 | 2.9869          | 0.3165 | 0.0728 | 0.1928 | 0.1926    | 122.652 |
| 3.1429        | 7.0   | 4375 | 2.9815          | 0.3189 | 0.0741 | 0.1935 | 0.1933    | 122.481 |
| 3.1226        | 8.0   | 5000 | 2.9761          | 0.3195 | 0.0755 | 0.194  | 0.1938    | 122.724 |
| 3.1259        | 9.0   | 5625 | 2.9747          | 0.3208 | 0.0755 | 0.1949 | 0.1947    | 122.551 |
| 3.1151        | 10.0  | 6250 | 2.9737          | 0.3207 | 0.0752 | 0.1949 | 0.1947    | 122.586 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0