---
license: apache-2.0
language:
- en
tags:
- generated_from_trainer
model-index:
- name: t5-small-finetuned-turk-text-simplification
  results: []
widget:
- text: "simplify: the incident has been the subject of numerous reports as to ethics in scholarship ."
- text: "simplify: the historical method comprises the techniques and guidelines by which historians use primary sources and other evidence to research and then to write history ."
- text: "simplify: none of the authors , contributors , sponsors , administrators , vandals , or anyone else connected with wikipedia , in any way whatsoever , can be responsible for your use of the information contained in or linked from these web pages ."
- text: "simplify: oregano is an indispensable ingredient in greek cuisine ."

inference:
  parameters:
    temperature: 1.5
    max_length: 256 
    do_sample: True
    num_beams: 3
 
---

<!-- 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-turk-text-simplification

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: 0.1001
- Rouge2 Precision: 0.6825
- Rouge2 Recall: 0.4542
- Rouge2 Fmeasure: 0.5221

## 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: 32
- eval_batch_size: 32
- 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 | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
| 0.4318        | 1.0   | 500  | 0.1053          | 0.682            | 0.4533        | 0.5214          |
| 0.0977        | 2.0   | 1000 | 0.1019          | 0.683            | 0.4545        | 0.5225          |
| 0.0938        | 3.0   | 1500 | 0.1010          | 0.6828           | 0.4547        | 0.5226          |
| 0.0916        | 4.0   | 2000 | 0.1003          | 0.6829           | 0.4545        | 0.5225          |
| 0.0906        | 5.0   | 2500 | 0.1001          | 0.6825           | 0.4542        | 0.5221          |


### Framework versions

- Transformers 4.21.3
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1