GroNLP/dutch-cola
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How to use HylkeBr/bertje_dutch-cola with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="HylkeBr/bertje_dutch-cola") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("HylkeBr/bertje_dutch-cola")
model = AutoModelForSequenceClassification.from_pretrained("HylkeBr/bertje_dutch-cola", device_map="auto")This model is a fine-tuned version of GroNLP/bert-base-dutch-cased on GroNLP/dutch-cola, from where only the acceptable and unacceptable examples were used to fine-tune. The data used for fine-tuning therefore only contains sentences with original mark 'None' and '*'.
Accuracy: 0.8127
The following hyperparameters were used during training:
learning rate: 4e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
num_epochs: 4
| Epoch | Training Loss | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.0 | 0.4971 | 1169 | 0.4629 | 0.7914 |
| 2.0 | 0.2478 | 2338 | 0.7041 | 0.7814 |
| 3.0 | 0.1333 | 3507 | 0.9777 | 0.8064 |
| 4.0 | 0.0687 | 4676 | 1.1322 | 0.8127 |