---
license: cc-by-sa-4.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: SloBertAA_Top100_WithOOC_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_Top100_WithOOC_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: 1.6326
- Accuracy: 0.7431
- F1: 0.7447
- Precision: 0.7503
- Recall: 0.7431

## 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.5143        | 1.0   | 45122  | 1.4964          | 0.6272   | 0.6264 | 0.6488    | 0.6272 |
| 1.2462        | 2.0   | 90244  | 1.2729          | 0.6811   | 0.6814 | 0.7043    | 0.6811 |
| 1.0236        | 3.0   | 135366 | 1.2134          | 0.7012   | 0.7027 | 0.7211    | 0.7012 |
| 0.7721        | 4.0   | 180488 | 1.1976          | 0.7179   | 0.7204 | 0.7357    | 0.7179 |
| 0.6597        | 5.0   | 225610 | 1.1953          | 0.7321   | 0.7324 | 0.7406    | 0.7321 |
| 0.4816        | 6.0   | 270732 | 1.2776          | 0.7303   | 0.7330 | 0.7444    | 0.7303 |
| 0.4039        | 7.0   | 315854 | 1.3625          | 0.7363   | 0.7379 | 0.7451    | 0.7363 |
| 0.2845        | 8.0   | 360976 | 1.4677          | 0.7395   | 0.7407 | 0.7470    | 0.7395 |
| 0.2192        | 9.0   | 406098 | 1.5720          | 0.7422   | 0.7434 | 0.7488    | 0.7422 |
| 0.1689        | 10.0  | 451220 | 1.6326          | 0.7431   | 0.7447 | 0.7503    | 0.7431 |


### Framework versions

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