---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: SloBertAA_Top50_WithOOC_082023_MultilingualBertBase
  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_Top50_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: 1.6735
- Accuracy: 0.7607
- F1: 0.7597
- Precision: 0.7600
- Recall: 0.7607

## 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.2345        | 1.0   | 33346  | 1.1611          | 0.6809   | 0.6782 | 0.6864    | 0.6809 |
| 0.9498        | 2.0   | 66692  | 1.0380          | 0.7149   | 0.7106 | 0.7257    | 0.7149 |
| 0.7929        | 3.0   | 100038 | 0.9825          | 0.7368   | 0.7340 | 0.7384    | 0.7368 |
| 0.6319        | 4.0   | 133384 | 0.9972          | 0.7453   | 0.7436 | 0.7480    | 0.7453 |
| 0.4944        | 5.0   | 166730 | 1.0890          | 0.7479   | 0.7461 | 0.7498    | 0.7479 |
| 0.3771        | 6.0   | 200076 | 1.1597          | 0.7523   | 0.7506 | 0.7518    | 0.7523 |
| 0.2644        | 7.0   | 233422 | 1.3175          | 0.7553   | 0.7538 | 0.7547    | 0.7553 |
| 0.1736        | 8.0   | 266768 | 1.4977          | 0.7559   | 0.7549 | 0.7575    | 0.7559 |
| 0.1184        | 9.0   | 300114 | 1.6160          | 0.7595   | 0.7579 | 0.7580    | 0.7595 |
| 0.0784        | 10.0  | 333460 | 1.6735          | 0.7607   | 0.7597 | 0.7600    | 0.7607 |


### Framework versions

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