---
tags:
- generated_from_keras_callback
model-index:
- name: Svenskmodell
  results: []
---

<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->

# Svenskmodell

This model is a fine-tuned version of [KB/bert-base-swedish-cased](https://huggingface.co/KB/bert-base-swedish-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.3411
- Train End Logits Accuracy: 0.8882
- Train Start Logits Accuracy: 0.8838
- Validation Loss: 1.4988
- Validation End Logits Accuracy: 0.6713
- Validation Start Logits Accuracy: 0.6669
- Epoch: 3

## 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:
- optimizer: {'name': 'Adam', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 28792, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Train End Logits Accuracy | Train Start Logits Accuracy | Validation Loss | Validation End Logits Accuracy | Validation Start Logits Accuracy | Epoch |
|:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:|
| 1.2392     | 0.6241                    | 0.6197                      | 1.0970          | 0.6588                         | 0.6543                           | 0     |
| 0.7549     | 0.7615                    | 0.7569                      | 1.1185          | 0.6673                         | 0.6665                           | 1     |
| 0.5005     | 0.8376                    | 0.8323                      | 1.3299          | 0.6571                         | 0.6503                           | 2     |
| 0.3411     | 0.8882                    | 0.8838                      | 1.4988          | 0.6713                         | 0.6669                           | 3     |


### Framework versions

- Transformers 4.20.1
- TensorFlow 2.6.4
- Datasets 2.1.0
- Tokenizers 0.12.1