---
license: cc-by-sa-4.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: SloBertAA_Top5_WithoutOOC_NEW
  results: []
datasets:
- gregorgabrovsek/RTVCommentsTop5UsersWithoutOOC
language:
- sl
---

<!-- 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_Top5_WithoutOOC_NEW

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: 0.3464
- Accuracy: 0.9419

## Other related models

| Base model          | Includes the OOC class? | 5 classes | 10 classes | 20 classes | 50 classes |
| ------------------- | ----------------------- |:---------:|:----------:|:----------:|:----------:|
| SloBERTa            | Yes                     | x | x | x | x |
| SloBERTa            | No                      | x | x | x | x |
| BERT Multilingual   | Yes                     | x | x | x | x |
| BERT Multilingual   | No                      | x | x | x | x |

## 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: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2787        | 1.0   | 8757  | 0.2899          | 0.9120   |
| 0.2197        | 2.0   | 17514 | 0.2314          | 0.9294   |
| 0.1483        | 3.0   | 26271 | 0.3004          | 0.9349   |
| 0.0997        | 4.0   | 35028 | 0.3182          | 0.9405   |
| 0.0699        | 5.0   | 43785 | 0.3464          | 0.9419   |


### Framework versions

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