DanskBERT_FGN / README.md
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---
license: cc-by-4.0
base_model: vesteinn/DanskBERT
tags:
- generated_from_trainer
model-index:
- name: DanskBERT_FGN
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# DanskBERT_FGN
This model is a fine-tuned version of [vesteinn/DanskBERT](https://huggingface.co/vesteinn/DanskBERT) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4535
- F1-score: 0.8102
## 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: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1-score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 120 | 0.6078 | 0.7542 |
| No log | 2.0 | 240 | 0.5319 | 0.7838 |
| No log | 3.0 | 360 | 0.7563 | 0.7942 |
| No log | 4.0 | 480 | 0.9098 | 0.7940 |
| 0.4909 | 5.0 | 600 | 1.2334 | 0.7728 |
| 0.4909 | 6.0 | 720 | 1.1453 | 0.7935 |
| 0.4909 | 7.0 | 840 | 1.2240 | 0.8017 |
| 0.4909 | 8.0 | 960 | 1.3105 | 0.7907 |
| 0.0877 | 9.0 | 1080 | 1.4305 | 0.8002 |
| 0.0877 | 10.0 | 1200 | 1.4420 | 0.7764 |
| 0.0877 | 11.0 | 1320 | 1.4535 | 0.8102 |
| 0.0877 | 12.0 | 1440 | 1.4482 | 0.7734 |
| 0.0326 | 13.0 | 1560 | 1.5240 | 0.8046 |
| 0.0326 | 14.0 | 1680 | 1.5290 | 0.8031 |
| 0.0326 | 15.0 | 1800 | 1.5302 | 0.7964 |
| 0.0326 | 16.0 | 1920 | 1.5503 | 0.7904 |
| 0.0159 | 17.0 | 2040 | 1.5510 | 0.7904 |
| 0.0159 | 18.0 | 2160 | 1.5714 | 0.7957 |
| 0.0159 | 19.0 | 2280 | 1.5932 | 0.7963 |
| 0.0159 | 20.0 | 2400 | 1.5998 | 0.7955 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1