metadata
base_model: GroNLP/bert-base-dutch-cased
tags:
- generated_from_trainer
metrics:
- f1
- precision
- recall
model-index:
- name: BERTje_finetuned_1994
results: []
BERTje_finetuned_1994
This model is a fine-tuned version of GroNLP/bert-base-dutch-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1184
- F1: 0.1799
- Precision: 0.1350
- Recall: 0.2698
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: 3
- eval_batch_size: 3
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 6
- 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 | F1 | Precision | Recall |
|---|---|---|---|---|---|---|
| No log | 1.0 | 110 | 0.2231 | 0.0522 | 0.0268 | 0.9688 |
| No log | 2.0 | 221 | 0.1446 | 0.1050 | 0.0576 | 0.5899 |
| No log | 3.0 | 331 | 0.1264 | 0.1726 | 0.1151 | 0.3452 |
| No log | 4.0 | 442 | 0.1201 | 0.1812 | 0.1350 | 0.2759 |
| 0.1954 | 4.98 | 550 | 0.1184 | 0.1799 | 0.1350 | 0.2698 |
Framework versions
- Transformers 4.35.0
- Pytorch 1.11.0+cu102
- Datasets 2.14.6
- Tokenizers 0.14.1