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---
license: cc-by-4.0
base_model: vesteinn/DanskBERT
tags:
- generated_from_trainer
model-index:
- name: MeMo_BERT-SA_DanskBERT
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. -->
# MeMo_BERT-SA_DanskBERT
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: 1.0740
- F1-score: 0.7498
## 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 | 297 | 0.6212 | 0.7242 |
| 0.6865 | 2.0 | 594 | 0.8063 | 0.7421 |
| 0.6865 | 3.0 | 891 | 0.8167 | 0.7366 |
| 0.4433 | 4.0 | 1188 | 1.3513 | 0.7479 |
| 0.4433 | 5.0 | 1485 | 1.0740 | 0.7498 |
| 0.2387 | 6.0 | 1782 | 1.6338 | 0.7128 |
| 0.0864 | 7.0 | 2079 | 1.7501 | 0.7032 |
| 0.0864 | 8.0 | 2376 | 2.1446 | 0.7137 |
| 0.0505 | 9.0 | 2673 | 2.2850 | 0.7117 |
| 0.0505 | 10.0 | 2970 | 2.2474 | 0.7430 |
| 0.0183 | 11.0 | 3267 | 2.2403 | 0.7315 |
| 0.023 | 12.0 | 3564 | 2.2304 | 0.7274 |
| 0.023 | 13.0 | 3861 | 2.3297 | 0.7304 |
| 0.0227 | 14.0 | 4158 | 2.3744 | 0.7338 |
| 0.0227 | 15.0 | 4455 | 2.3618 | 0.7383 |
| 0.0113 | 16.0 | 4752 | 2.2777 | 0.7457 |
| 0.0058 | 17.0 | 5049 | 2.3752 | 0.7440 |
| 0.0058 | 18.0 | 5346 | 2.4774 | 0.7406 |
| 0.0019 | 19.0 | 5643 | 2.3590 | 0.7451 |
| 0.0019 | 20.0 | 5940 | 2.3930 | 0.7477 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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