---
license: cc-by-sa-4.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: SloBertAA_Top20_WithoutOOC_082023
  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. -->

# SloBertAA_Top20_WithoutOOC_082023

This model is a fine-tuned version of [EMBEDDIA/sloberta](https://huggingface.co/EMBEDDIA/sloberta) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8485
- Accuracy: 0.8909
- F1: 0.8908
- Precision: 0.8914
- Recall: 0.8909

## 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: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:------:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.5035        | 1.0   | 22717  | 0.4645          | 0.8498   | 0.8495 | 0.8603    | 0.8498 |
| 0.3863        | 2.0   | 45434  | 0.4249          | 0.8679   | 0.8680 | 0.8703    | 0.8679 |
| 0.3005        | 3.0   | 68151  | 0.4785          | 0.8695   | 0.8700 | 0.8743    | 0.8695 |
| 0.2094        | 4.0   | 90868  | 0.5345          | 0.8771   | 0.8769 | 0.8801    | 0.8771 |
| 0.1878        | 5.0   | 113585 | 0.6158          | 0.8793   | 0.8792 | 0.8817    | 0.8793 |
| 0.1256        | 6.0   | 136302 | 0.6737          | 0.8847   | 0.8847 | 0.8860    | 0.8847 |
| 0.0999        | 7.0   | 159019 | 0.7364          | 0.8855   | 0.8857 | 0.8870    | 0.8855 |
| 0.0633        | 8.0   | 181736 | 0.8041          | 0.8863   | 0.8862 | 0.8874    | 0.8863 |
| 0.0338        | 9.0   | 204453 | 0.8479          | 0.8877   | 0.8877 | 0.8891    | 0.8877 |
| 0.0178        | 10.0  | 227170 | 0.8485          | 0.8909   | 0.8908 | 0.8914    | 0.8909 |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.8.0
- Datasets 2.10.1
- Tokenizers 0.13.2