---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: MBERT_uncased_GeneralizedCrossEntropy_full_ft
  results: []
---

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# MBERT_uncased_GeneralizedCrossEntropy_full_ft

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:
- Accuracy: 0.802
- F1: 0.8584
- Precision: 0.8310
- Recall: 0.8876
- Roc Auc: 0.7555
- Loss: 0.2729

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Accuracy | F1     | Precision | Recall | Roc Auc | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:------:|:---------:|:------:|:-------:|:---------------:|
| No log        | 0.992 | 62   | 0.77     | 0.8487 | 0.7642    | 0.9541 | 0.6700  | 0.3336          |
| 0.3578        | 2.0   | 125  | 0.805    | 0.8567 | 0.8511    | 0.8624 | 0.7738  | 0.2695          |
| 0.3578        | 2.976 | 186  | 0.802    | 0.8584 | 0.8310    | 0.8876 | 0.7555  | 0.2729          |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3