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---
license: apache-2.0
base_model: alexanderfalk/danbert-small-cased
tags:
- generated_from_trainer
model-index:
- name: MeMo_BERT-SA_danbert
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_danbert
This model is a fine-tuned version of [alexanderfalk/danbert-small-cased](https://huggingface.co/alexanderfalk/danbert-small-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.4690
- F1-score: 0.6544
## 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 | 1.0065 | 0.5054 |
| 0.8685 | 2.0 | 594 | 1.0551 | 0.5964 |
| 0.8685 | 3.0 | 891 | 1.3189 | 0.5761 |
| 0.3832 | 4.0 | 1188 | 2.0270 | 0.6322 |
| 0.3832 | 5.0 | 1485 | 2.1568 | 0.6076 |
| 0.1519 | 6.0 | 1782 | 3.3066 | 0.5763 |
| 0.0403 | 7.0 | 2079 | 3.1085 | 0.6049 |
| 0.0403 | 8.0 | 2376 | 3.1069 | 0.6269 |
| 0.009 | 9.0 | 2673 | 3.2610 | 0.6213 |
| 0.009 | 10.0 | 2970 | 3.3529 | 0.6355 |
| 0.0123 | 11.0 | 3267 | 3.4172 | 0.6306 |
| 0.0089 | 12.0 | 3564 | 3.4950 | 0.6187 |
| 0.0089 | 13.0 | 3861 | 3.7618 | 0.6117 |
| 0.0053 | 14.0 | 4158 | 3.5352 | 0.6252 |
| 0.0053 | 15.0 | 4455 | 3.7667 | 0.6120 |
| 0.0047 | 16.0 | 4752 | 3.4690 | 0.6544 |
| 0.0059 | 17.0 | 5049 | 3.6646 | 0.6256 |
| 0.0059 | 18.0 | 5346 | 3.6611 | 0.6319 |
| 0.0018 | 19.0 | 5643 | 3.7555 | 0.6423 |
| 0.0018 | 20.0 | 5940 | 3.7564 | 0.6422 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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