---
license: apache-2.0
tags:
- generated_from_trainer
pipeline_tag: text2text-generation
inference:
  parameters:
    max_length: 256
    num_beams: 4
    length_penalty: 1.5
    no_repeat_ngram_size: 3
    early_stopping: true
base_model: yhavinga/t5-base-dutch
model-index:
- name: t5-end2end-questions-generation-dutch
  results: []
---



# t5-end2end-questions-generation-dutch

This model is a fine-tuned version of [yhavinga/t5-base-dutch](https://huggingface.co/yhavinga/t5-base-dutch) on a 
Google translated version of SQUAD 1.1 found here: https://www.kaggle.com/datasets/michelvanheijningen/squad1-dutch. 

The code used to finetune the model is largely based on the work by Thomas Simonini. You can find his English model 
[here](https://huggingface.co/ThomasSimonini/t5-end2end-question-generation) and his Google colab tutorial [here](https://colab.research.google.com/drive/1z-Zl2hftMrFXabYfmz8o9YZpgYx6sGeW?usp=sharing)

It achieves the following results on the evaluation set:
- Loss: 1.6546

## Model description

This is my first model ever and still a work in progress ;) 

## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.6528        | 0.34  | 100  | 1.9249          |
| 1.964         | 0.68  | 200  | 1.7897          |
| 1.8695        | 1.02  | 300  | 1.7554          |
| 1.7922        | 1.35  | 400  | 1.7270          |
| 1.7747        | 1.69  | 500  | 1.7054          |
| 1.7473        | 2.03  | 600  | 1.7019          |
| 1.697         | 2.37  | 700  | 1.6868          |
| 1.6848        | 2.71  | 800  | 1.6810          |
| 1.6756        | 3.05  | 900  | 1.6779          |
| 1.6282        | 3.39  | 1000 | 1.6712          |
| 1.6285        | 3.73  | 1100 | 1.6626          |
| 1.6161        | 4.06  | 1200 | 1.6616          |
| 1.5887        | 4.4   | 1300 | 1.6588          |
| 1.5877        | 4.74  | 1400 | 1.6583          |
| 1.5723        | 5.08  | 1500 | 1.6560          |
| 1.5545        | 5.42  | 1600 | 1.6550          |
| 1.5415        | 5.76  | 1700 | 1.6540          |
| 1.5509        | 6.1   | 1800 | 1.6541          |
| 1.5326        | 6.44  | 1900 | 1.6539          |
| 1.5268        | 6.77  | 2000 | 1.6546          |


### Framework versions

- Transformers 4.27.4
- Pytorch 1.13.0
- Datasets 2.1.0
- Tokenizers 0.13.2