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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: t5-end2end-questions-generation-dutch |
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results: [] |
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pipeline_tag: text2text-generation |
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inference: |
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parameters: |
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max_length: 256 |
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num_beams: 4 |
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length_penalty: 1.5 |
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no_repeat_ngram_size: 3 |
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early_stopping: True |
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--- |
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# t5-end2end-questions-generation-dutch |
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This model is a fine-tuned version of [yhavinga/t5-base-dutch](https://huggingface.co/yhavinga/t5-base-dutch) on a |
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Google translated version of SQUAD 1.1 found here: https://www.kaggle.com/datasets/michelvanheijningen/squad1-dutch. |
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The code used to finetune the model is largely based on the work by Thomas Simonini. You can find his English model |
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[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) |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6546 |
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## Model description |
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This is my first model ever and still a work in progress ;) |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 7 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 2.6528 | 0.34 | 100 | 1.9249 | |
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| 1.964 | 0.68 | 200 | 1.7897 | |
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| 1.8695 | 1.02 | 300 | 1.7554 | |
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| 1.7922 | 1.35 | 400 | 1.7270 | |
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| 1.7747 | 1.69 | 500 | 1.7054 | |
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| 1.7473 | 2.03 | 600 | 1.7019 | |
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| 1.697 | 2.37 | 700 | 1.6868 | |
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| 1.6848 | 2.71 | 800 | 1.6810 | |
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| 1.6756 | 3.05 | 900 | 1.6779 | |
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| 1.6282 | 3.39 | 1000 | 1.6712 | |
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| 1.6285 | 3.73 | 1100 | 1.6626 | |
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| 1.6161 | 4.06 | 1200 | 1.6616 | |
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| 1.5887 | 4.4 | 1300 | 1.6588 | |
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| 1.5877 | 4.74 | 1400 | 1.6583 | |
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| 1.5723 | 5.08 | 1500 | 1.6560 | |
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| 1.5545 | 5.42 | 1600 | 1.6550 | |
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| 1.5415 | 5.76 | 1700 | 1.6540 | |
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| 1.5509 | 6.1 | 1800 | 1.6541 | |
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| 1.5326 | 6.44 | 1900 | 1.6539 | |
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| 1.5268 | 6.77 | 2000 | 1.6546 | |
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### Framework versions |
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- Transformers 4.27.4 |
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- Pytorch 1.13.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.13.2 |
