metadata
license: cc-by-4.0
base_model: Maltehb/danish-bert-botxo
tags:
- generated_from_trainer
metrics:
- f1
- precision
- recall
- accuracy
model-index:
- name: bert-finetuned-danishboksen
results: []
bert-finetuned-danishboksen
This model is a fine-tuned version of Maltehb/danish-bert-botxo on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4854
- F1: 0.5556
- Precision: 0.5
- Recall: 0.6667
- Accuracy: 0.6667
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Precision | Recall | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.9427 | 1.0 | 6 | 0.8937 | 0.5556 | 0.5 | 0.6667 | 0.6667 |
| 0.611 | 2.0 | 12 | 0.7647 | 0.5556 | 0.5 | 0.6667 | 0.6667 |
| 0.3739 | 3.0 | 18 | 0.4088 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.2494 | 4.0 | 24 | 0.4639 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.1707 | 5.0 | 30 | 0.4854 | 0.5556 | 0.5 | 0.6667 | 0.6667 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1