---
license: agpl-3.0
base_model: vesteinn/ScandiBERT
tags:
- generated_from_trainer
model-index:
- name: MeMo_BERT-WSD-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-WSD-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: 2.0491
- F1-score: 0.4001

## 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   | 61   | 1.3760          | 0.1229   |
| No log        | 2.0   | 122  | 1.4064          | 0.1229   |
| No log        | 3.0   | 183  | 1.4753          | 0.1229   |
| No log        | 4.0   | 244  | 1.3255          | 0.1229   |
| No log        | 5.0   | 305  | 1.3649          | 0.1229   |
| No log        | 6.0   | 366  | 1.3784          | 0.1229   |
| No log        | 7.0   | 427  | 1.3312          | 0.2191   |
| No log        | 8.0   | 488  | 1.3717          | 0.1229   |
| 1.2808        | 9.0   | 549  | 1.5063          | 0.1229   |
| 1.2808        | 10.0  | 610  | 1.2576          | 0.3721   |
| 1.2808        | 11.0  | 671  | 1.4630          | 0.3622   |
| 1.2808        | 12.0  | 732  | 1.7778          | 0.3258   |
| 1.2808        | 13.0  | 793  | 2.2233          | 0.3402   |
| 1.2808        | 14.0  | 854  | 2.1684          | 0.3619   |
| 1.2808        | 15.0  | 915  | 2.0034          | 0.3668   |
| 1.2808        | 16.0  | 976  | 1.8374          | 0.3818   |
| 0.9251        | 17.0  | 1037 | 1.9104          | 0.3956   |
| 0.9251        | 18.0  | 1098 | 2.0491          | 0.4001   |
| 0.9251        | 19.0  | 1159 | 2.1429          | 0.3534   |
| 0.9251        | 20.0  | 1220 | 2.1352          | 0.3648   |


### Framework versions

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