robbertfinetuned0906
This model is a fine-tuned version of pdelobelle/robbert-v2-dutch-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5859
- Precision: 0.7151
- Recall: 0.7079
- F1: 0.7115
- Accuracy: 0.9186
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.046 | 1.0 | 580 | 0.5770 | 0.6912 | 0.6633 | 0.6769 | 0.9102 |
| 0.0405 | 2.0 | 1160 | 0.5704 | 0.6996 | 0.6835 | 0.6914 | 0.9133 |
| 0.0346 | 3.0 | 1740 | 0.5786 | 0.6951 | 0.7201 | 0.7074 | 0.9130 |
| 0.0242 | 4.0 | 2320 | 0.5453 | 0.7098 | 0.7216 | 0.7157 | 0.9186 |
| 0.0184 | 5.0 | 2900 | 0.6058 | 0.7118 | 0.7036 | 0.7077 | 0.9189 |
| 0.0087 | 6.0 | 3480 | 0.5859 | 0.7151 | 0.7079 | 0.7115 | 0.9186 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3