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---
base_model: MiMe-MeMo/MeMo-BERT-03
tags:
- generated_from_trainer
model-index:
- name: MeMo_BERT-SA
results: []
language: da
widget:
- text: >-
Men endnu sad hun , bleg og skælvende , ved vinduet og lyttede med rædsel i sit blikat en den urolige i de !
---
<!-- 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
This model is a fine-tuned version of [MiMe-MeMo/MeMo-BERT-03](https://huggingface.co/MiMe-MeMo/MeMo-BERT-03) on an https://huggingface.co/MiMe-MeMo/MeMo-Dataset-SA dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3157
- F1-score: 0.7821
## 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 | 0.7332 | 0.7373 |
| 0.5945 | 2.0 | 594 | 0.9941 | 0.7644 |
| 0.5945 | 3.0 | 891 | 1.1745 | 0.7714 |
| 0.2243 | 4.0 | 1188 | 1.6828 | 0.7210 |
| 0.2243 | 5.0 | 1485 | 1.6114 | 0.7308 |
| 0.0807 | 6.0 | 1782 | 1.9495 | 0.7515 |
| 0.0133 | 7.0 | 2079 | 2.0289 | 0.7536 |
| 0.0133 | 8.0 | 2376 | 2.1528 | 0.7566 |
| 0.0002 | 9.0 | 2673 | 2.2011 | 0.7560 |
| 0.0002 | 10.0 | 2970 | 2.2830 | 0.7351 |
| 0.0199 | 11.0 | 3267 | 2.3461 | 0.7456 |
| 0.0103 | 12.0 | 3564 | 2.2212 | 0.7533 |
| 0.0103 | 13.0 | 3861 | 2.2322 | 0.7622 |
| 0.0063 | 14.0 | 4158 | 2.3226 | 0.7599 |
| 0.0063 | 15.0 | 4455 | 2.3019 | 0.7561 |
| 0.0026 | 16.0 | 4752 | 2.2407 | 0.7675 |
| 0.0 | 17.0 | 5049 | 2.2745 | 0.7715 |
| 0.0 | 18.0 | 5346 | 2.3114 | 0.7716 |
| 0.0002 | 19.0 | 5643 | 2.3157 | 0.7821 |
| 0.0002 | 20.0 | 5940 | 2.3187 | 0.7749 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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