---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: SloBertAA_Top100_WithoutOOC_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_WithoutOOC_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: 1.8490
- Accuracy: 0.6964
- F1: 0.6972
- Precision: 0.7001
- Recall: 0.6964

## 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.6988        | 1.0   | 44675  | 1.6287          | 0.5883   | 0.5902 | 0.6087    | 0.5883 |
| 1.3829        | 2.0   | 89350  | 1.4305          | 0.6351   | 0.6379 | 0.6563    | 0.6351 |
| 1.1122        | 3.0   | 134025 | 1.3339          | 0.6635   | 0.6651 | 0.6774    | 0.6635 |
| 0.881         | 4.0   | 178700 | 1.3128          | 0.6799   | 0.6805 | 0.6876    | 0.6799 |
| 0.7032        | 5.0   | 223375 | 1.3628          | 0.6831   | 0.6840 | 0.6932    | 0.6831 |
| 0.5454        | 6.0   | 268050 | 1.4343          | 0.6877   | 0.6890 | 0.6956    | 0.6877 |
| 0.408         | 7.0   | 312725 | 1.5546          | 0.6877   | 0.6888 | 0.6958    | 0.6877 |
| 0.2752        | 8.0   | 357400 | 1.6623          | 0.6932   | 0.6948 | 0.6992    | 0.6932 |
| 0.1844        | 9.0   | 402075 | 1.7825          | 0.6947   | 0.6959 | 0.6995    | 0.6947 |
| 0.1506        | 10.0  | 446750 | 1.8490          | 0.6964   | 0.6972 | 0.7001    | 0.6964 |


### Framework versions

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