---
license: agpl-3.0
base_model: vesteinn/ScandiBERT
tags:
- generated_from_trainer
model-index:
- name: MeMo_BERT-SA_ScandiBERT
  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_ScandiBERT

This model is a fine-tuned version of [vesteinn/ScandiBERT](https://huggingface.co/vesteinn/ScandiBERT) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1392
- F1-score: 0.7266

## 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  | 0.8686          | 0.6373   |
| 0.8175        | 2.0   | 594  | 0.8961          | 0.7140   |
| 0.8175        | 3.0   | 891  | 0.8175          | 0.7237   |
| 0.5748        | 4.0   | 1188 | 1.2192          | 0.7226   |
| 0.5748        | 5.0   | 1485 | 1.1315          | 0.7003   |
| 0.3963        | 6.0   | 1782 | 1.3036          | 0.6791   |
| 0.2579        | 7.0   | 2079 | 1.2430          | 0.7100   |
| 0.2579        | 8.0   | 2376 | 1.7559          | 0.7143   |
| 0.1768        | 9.0   | 2673 | 1.8862          | 0.7070   |
| 0.1768        | 10.0  | 2970 | 1.9733          | 0.7137   |
| 0.1065        | 11.0  | 3267 | 2.2073          | 0.7071   |
| 0.0559        | 12.0  | 3564 | 2.1912          | 0.7184   |
| 0.0559        | 13.0  | 3861 | 2.1392          | 0.7266   |
| 0.0367        | 14.0  | 4158 | 2.3618          | 0.6950   |
| 0.0367        | 15.0  | 4455 | 2.3324          | 0.7223   |
| 0.026         | 16.0  | 4752 | 2.4711          | 0.7108   |
| 0.0041        | 17.0  | 5049 | 2.5320          | 0.7108   |
| 0.0041        | 18.0  | 5346 | 2.6578          | 0.6948   |
| 0.0059        | 19.0  | 5643 | 2.6631          | 0.6991   |
| 0.0059        | 20.0  | 5940 | 2.6313          | 0.7067   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2