---
library_name: transformers
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mBERT-2
  results: []
language:
- cs
---

<!-- 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. -->

# mBERT-2

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the CERED(Czech Relationship Extraction dataset)-version-2 dataset. (https://lindat.mff.cuni.cz/repository/xmlui/handle/11234/1-3266?locale-attribute=cs)
It achieves the following results on the test set:
- Loss: 0.9469
- Accuracy: 0.8845
- Micro Precision: 0.8845
- Micro Recall: 0.8845
- Micro F1: 0.8845
- Macro Precision: 0.8512
- Macro Recall: 0.8349
- Macro F1: 0.8398

## 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: 5e-05
- train_batch_size: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy | Micro Precision | Micro Recall | Micro F1 | Macro Precision | Macro Recall | Macro F1 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|:---------------:|:------------:|:--------:|:---------------:|:------------:|:--------:|
| 0.6019        | 1.0   | 30148  | 0.5612          | 0.8398   | 0.8398          | 0.8398       | 0.8398   | 0.8271          | 0.7687       | 0.7761   |
| 0.4904        | 2.0   | 60296  | 0.5216          | 0.8564   | 0.8564          | 0.8564       | 0.8564   | 0.8172          | 0.8079       | 0.8032   |
| 0.3624        | 3.0   | 90444  | 0.5196          | 0.8656   | 0.8656          | 0.8656       | 0.8656   | 0.8374          | 0.8006       | 0.8094   |
| 0.3242        | 4.0   | 120592 | 0.5662          | 0.8720   | 0.8720          | 0.8720       | 0.8720   | 0.8468          | 0.8222       | 0.8275   |
| 0.2522        | 5.0   | 150740 | 0.6456          | 0.8717   | 0.8717          | 0.8717       | 0.8717   | 0.8329          | 0.8374       | 0.8298   |
| 0.1707        | 6.0   | 180888 | 0.7233          | 0.8764   | 0.8764          | 0.8764       | 0.8764   | 0.8442          | 0.8356       | 0.8343   |
| 0.103         | 7.0   | 211036 | 0.8474          | 0.8794   | 0.8794          | 0.8794       | 0.8794   | 0.8440          | 0.8403       | 0.8385   |
| 0.0646        | 8.0   | 241184 | 0.9117          | 0.8836   | 0.8836          | 0.8836       | 0.8836   | 0.8465          | 0.8455       | 0.8423   |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3