---
library_name: transformers
base_model: KBLab/bert-base-swedish-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: educational_score_bert_swe
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# educational_score_bert_swe

This model is a fine-tuned version of [KBLab/bert-base-swedish-cased](https://huggingface.co/KBLab/bert-base-swedish-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1310
- Accuracy: 0.5562
- F1 Weighted: 0.5335

## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Weighted |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|
| 1.1786        | 1.0   | 2944 | 1.1540          | 0.5173   | 0.4826      |
| 1.0685        | 2.0   | 5888 | 1.1555          | 0.5182   | 0.4934      |
| 0.8442        | 3.0   | 8832 | 1.2582          | 0.5042   | 0.4928      |


### Framework versions

- Transformers 4.55.0
- Pytorch 2.5.1+cu121
- Datasets 4.0.0
- Tokenizers 0.21.4