---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: fosh-detector-v2-tmp
  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. -->

# fosh-detector-v2-tmp

This model is a fine-tuned version of [google-bert/bert-base-multilingual-uncased](https://huggingface.co/google-bert/bert-base-multilingual-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1027
- Accuracy: 0.9684
- Precision: 0.8378
- Recall: 0.8692
- F1: 0.8532

## 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: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Use OptimizerNames.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: 4

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.3176        | 0.1305 | 50   | 0.2282          | 0.9150   | 0.6981    | 0.3458 | 0.4625 |
| 0.1735        | 0.2611 | 100  | 0.1324          | 0.9526   | 0.8242    | 0.7009 | 0.7576 |
| 0.1358        | 0.3916 | 150  | 0.1283          | 0.9615   | 0.8542    | 0.7664 | 0.8079 |
| 0.1332        | 0.5222 | 200  | 0.1142          | 0.9664   | 0.8411    | 0.8411 | 0.8411 |
| 0.1125        | 0.6527 | 250  | 0.1268          | 0.9634   | 0.85      | 0.7944 | 0.8213 |
| 0.1022        | 0.7833 | 300  | 0.1251          | 0.9644   | 0.7983    | 0.8879 | 0.8407 |
| 0.1107        | 0.9138 | 350  | 0.0972          | 0.9644   | 0.8381    | 0.8224 | 0.8302 |
| 0.1017        | 1.0444 | 400  | 0.1070          | 0.9654   | 0.8396    | 0.8318 | 0.8357 |
| 0.0925        | 1.1749 | 450  | 0.0977          | 0.9664   | 0.8288    | 0.8598 | 0.8440 |
| 0.0834        | 1.3055 | 500  | 0.0867          | 0.9674   | 0.8936    | 0.7850 | 0.8358 |
| 0.0748        | 1.4360 | 550  | 0.0951          | 0.9704   | 0.8348    | 0.8972 | 0.8649 |
| 0.0697        | 1.5666 | 600  | 0.0950          | 0.9713   | 0.8611    | 0.8692 | 0.8651 |
| 0.0818        | 1.6971 | 650  | 0.0871          | 0.9674   | 0.8136    | 0.8972 | 0.8533 |
| 0.073         | 1.8277 | 700  | 0.0813          | 0.9684   | 0.8319    | 0.8785 | 0.8545 |
| 0.0742        | 1.9582 | 750  | 0.0841          | 0.9713   | 0.875     | 0.8505 | 0.8626 |
| 0.0599        | 2.0888 | 800  | 0.0926          | 0.9713   | 0.8824    | 0.8411 | 0.8612 |
| 0.0522        | 2.2193 | 850  | 0.1015          | 0.9674   | 0.8426    | 0.8505 | 0.8465 |
| 0.0581        | 2.3499 | 900  | 0.1000          | 0.9694   | 0.88      | 0.8224 | 0.8502 |
| 0.0562        | 2.4804 | 950  | 0.1066          | 0.9674   | 0.8364    | 0.8598 | 0.8479 |
| 0.0553        | 2.6110 | 1000 | 0.0989          | 0.9674   | 0.8190    | 0.8879 | 0.8520 |
| 0.0546        | 2.7415 | 1050 | 0.0921          | 0.9694   | 0.8725    | 0.8318 | 0.8517 |
| 0.0541        | 2.8721 | 1100 | 0.0920          | 0.9644   | 0.8034    | 0.8785 | 0.8393 |
| 0.0494        | 3.0026 | 1150 | 0.0981          | 0.9713   | 0.8611    | 0.8692 | 0.8651 |
| 0.0358        | 3.1332 | 1200 | 0.1033          | 0.9713   | 0.8679    | 0.8598 | 0.8638 |
| 0.038         | 3.2637 | 1250 | 0.1109          | 0.9684   | 0.8378    | 0.8692 | 0.8532 |
| 0.0408        | 3.3943 | 1300 | 0.0996          | 0.9684   | 0.8205    | 0.8972 | 0.8571 |
| 0.0456        | 3.5248 | 1350 | 0.0976          | 0.9684   | 0.8440    | 0.8598 | 0.8519 |
| 0.0367        | 3.6554 | 1400 | 0.1075          | 0.9694   | 0.8455    | 0.8692 | 0.8571 |
| 0.0332        | 3.7859 | 1450 | 0.1081          | 0.9684   | 0.8440    | 0.8598 | 0.8519 |
| 0.0376        | 3.9164 | 1500 | 0.1027          | 0.9684   | 0.8378    | 0.8692 | 0.8532 |


### Framework versions

- Transformers 4.50.3
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.1