---
license: apache-2.0
base_model: yhavinga/t5-base-dutch
tags:
- summarization dutch for keyword extraction from new
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-base-dutch-finetuned-mt5_base_keyword_extraction_dutch
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# t5-base-dutch-finetuned-mt5_base_keyword_extraction_dutch

This model is a fine-tuned version of [yhavinga/t5-base-dutch](https://huggingface.co/yhavinga/t5-base-dutch) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6065
- Rouge1: 0.7675
- Rouge2: 0.5965
- Rougel: 0.7531
- Rougelsum: 0.7534

## 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: 5.6e-05
- train_batch_size: 14
- eval_batch_size: 14
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 28
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| No log        | 1.0   | 94   | 1.2820          | 0.4332 | 0.3007 | 0.4175 | 0.4174    |
| 1.4828        | 2.0   | 188  | 0.9360          | 0.6075 | 0.4541 | 0.5916 | 0.5912    |
| 1.4828        | 3.0   | 282  | 0.7435          | 0.6542 | 0.4825 | 0.6358 | 0.6366    |
| 0.7633        | 4.0   | 376  | 0.6623          | 0.6867 | 0.5071 | 0.6692 | 0.6697    |
| 0.7633        | 5.0   | 470  | 0.6481          | 0.7061 | 0.5254 | 0.6909 | 0.6913    |
| 0.5935        | 6.0   | 564  | 0.6456          | 0.7155 | 0.5367 | 0.6984 | 0.6995    |
| 0.5935        | 7.0   | 658  | 0.6387          | 0.7162 | 0.5388 | 0.6993 | 0.7001    |
| 0.5101        | 8.0   | 752  | 0.6341          | 0.7247 | 0.5495 | 0.7086 | 0.7102    |
| 0.5101        | 9.0   | 846  | 0.6306          | 0.7335 | 0.5527 | 0.7166 | 0.7176    |
| 0.4449        | 10.0  | 940  | 0.6412          | 0.7324 | 0.5559 | 0.7160 | 0.7166    |
| 0.4449        | 11.0  | 1034 | 0.6439          | 0.7273 | 0.5513 | 0.7126 | 0.7136    |
| 0.4001        | 12.0  | 1128 | 0.6294          | 0.7415 | 0.5644 | 0.7266 | 0.7268    |
| 0.4001        | 13.0  | 1222 | 0.6252          | 0.7447 | 0.5658 | 0.7294 | 0.7296    |
| 0.3589        | 14.0  | 1316 | 0.6257          | 0.7490 | 0.5743 | 0.7341 | 0.7347    |
| 0.3589        | 15.0  | 1410 | 0.6132          | 0.7474 | 0.5751 | 0.7339 | 0.7346    |
| 0.3263        | 16.0  | 1504 | 0.6119          | 0.7616 | 0.5858 | 0.7469 | 0.7470    |
| 0.3263        | 17.0  | 1598 | 0.6088          | 0.7674 | 0.5945 | 0.7527 | 0.7530    |
| 0.2989        | 18.0  | 1692 | 0.6108          | 0.7655 | 0.5917 | 0.7510 | 0.7514    |
| 0.2989        | 19.0  | 1786 | 0.6020          | 0.7681 | 0.5961 | 0.7539 | 0.7545    |
| 0.2846        | 20.0  | 1880 | 0.6065          | 0.7675 | 0.5965 | 0.7531 | 0.7534    |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2