---
library_name: transformers
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mBERT-4
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# mBERT-4

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5499
- Accuracy: 0.8737
- Micro Precision: 0.8737
- Micro Recall: 0.8737
- Micro F1: 0.8737
- Macro Precision: 0.7217
- Macro Recall: 0.7435
- Macro F1: 0.7211

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:------------:|:--------:|:---------------:|:------------:|:--------:|
| 1.4916        | 1.0   | 868  | 0.6403          | 0.8      | 0.8             | 0.8          | 0.8      | 0.4830          | 0.4893       | 0.4736   |
| 0.7293        | 2.0   | 1736 | 0.4581          | 0.8684   | 0.8684          | 0.8684       | 0.8684   | 0.6734          | 0.6721       | 0.6634   |
| 0.5325        | 3.0   | 2604 | 0.4473          | 0.8632   | 0.8632          | 0.8632       | 0.8632   | 0.7108          | 0.7176       | 0.7076   |
| 0.4271        | 4.0   | 3472 | 0.5030          | 0.8737   | 0.8737          | 0.8737       | 0.8737   | 0.7014          | 0.7087       | 0.6965   |
| 0.29          | 5.0   | 4340 | 0.5381          | 0.8737   | 0.8737          | 0.8737       | 0.8737   | 0.7069          | 0.6907       | 0.6923   |
| 0.2108        | 6.0   | 5208 | 0.5382          | 0.8895   | 0.8895          | 0.8895       | 0.8895   | 0.7234          | 0.7560       | 0.7216   |
| 0.1264        | 7.0   | 6076 | 0.5208          | 0.8842   | 0.8842          | 0.8842       | 0.8842   | 0.7110          | 0.7488       | 0.7165   |
| 0.1054        | 8.0   | 6944 | 0.5499          | 0.8737   | 0.8737          | 0.8737       | 0.8737   | 0.7217          | 0.7435       | 0.7211   |


### Framework versions

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