metadata
library_name: transformers
license: mit
base_model: DTAI-KULeuven/robbert-2023-dutch-large
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: robbert-2023-dutch-large-topic_classification
results: []
robbert-2023-dutch-large-topic_classification
This model is a fine-tuned version of DTAI-KULeuven/robbert-2023-dutch-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7479
- Precision: 0.9198
- Recall: 0.9008
- F1: 0.9082
- Accuracy: 0.9118
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 88 | 0.7486 | 0.8471 | 0.8101 | 0.8223 | 0.8333 |
| No log | 2.0 | 176 | 0.7488 | 0.8557 | 0.7525 | 0.7800 | 0.8137 |
| No log | 3.0 | 264 | 0.9650 | 0.8507 | 0.8430 | 0.8347 | 0.8284 |
| No log | 4.0 | 352 | 0.7878 | 0.8982 | 0.8472 | 0.8650 | 0.8775 |
| No log | 5.0 | 440 | 0.8113 | 0.9254 | 0.8876 | 0.9020 | 0.9020 |
| 0.5488 | 6.0 | 528 | 0.8695 | 0.9070 | 0.8858 | 0.8936 | 0.8971 |
| 0.5488 | 7.0 | 616 | 0.7924 | 0.9174 | 0.8886 | 0.8983 | 0.9020 |
| 0.5488 | 8.0 | 704 | 0.6974 | 0.9198 | 0.9008 | 0.9082 | 0.9118 |
| 0.5488 | 9.0 | 792 | 0.7410 | 0.9292 | 0.9065 | 0.9148 | 0.9167 |
| 0.5488 | 10.0 | 880 | 0.7479 | 0.9198 | 0.9008 | 0.9082 | 0.9118 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1