---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: SloBertAA_Top100_WithOOC_082023_MultilingualBertBase
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# SloBertAA_Top100_WithOOC_082023_MultilingualBertBase

This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8608
- Accuracy: 0.6898
- F1: 0.6904
- Precision: 0.6936
- Recall: 0.6898

## 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.7313        | 1.0   | 45122  | 1.6826          | 0.5773   | 0.5766 | 0.5997    | 0.5773 |
| 1.4117        | 2.0   | 90244  | 1.4419          | 0.6341   | 0.6345 | 0.6529    | 0.6341 |
| 1.1573        | 3.0   | 135366 | 1.3509          | 0.6614   | 0.6620 | 0.6733    | 0.6614 |
| 0.9147        | 4.0   | 180488 | 1.3583          | 0.6695   | 0.6699 | 0.6817    | 0.6695 |
| 0.7452        | 5.0   | 225610 | 1.3881          | 0.6797   | 0.6800 | 0.6887    | 0.6797 |
| 0.5393        | 6.0   | 270732 | 1.4650          | 0.6828   | 0.6835 | 0.6897    | 0.6828 |
| 0.4207        | 7.0   | 315854 | 1.5770          | 0.6839   | 0.6840 | 0.6905    | 0.6839 |
| 0.2985        | 8.0   | 360976 | 1.6813          | 0.6869   | 0.6877 | 0.6921    | 0.6869 |
| 0.2029        | 9.0   | 406098 | 1.7977          | 0.6882   | 0.6886 | 0.6923    | 0.6882 |
| 0.1546        | 10.0  | 451220 | 1.8608          | 0.6898   | 0.6904 | 0.6936    | 0.6898 |


### Framework versions

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