---
library_name: transformers
license: apache-2.0
base_model: bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: SA_Model_bert-base-multilingual-uncased
  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. -->

# SA_Model_bert-base-multilingual-uncased

This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6256
- Accuracy: 0.9000
- Precision: 0.8995
- Recall: 0.9000
- F1: 0.8998

## 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: 16
- eval_batch_size: 16
- 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
- lr_scheduler_warmup_steps: 100
- num_epochs: 6
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.4675        | 1.0   | 2004  | 0.3975          | 0.8631   | 0.8637    | 0.8631 | 0.8630 |
| 0.36          | 2.0   | 4008  | 0.3589          | 0.8695   | 0.8781    | 0.8695 | 0.8719 |
| 0.2715        | 3.0   | 6012  | 0.4023          | 0.8822   | 0.8840    | 0.8822 | 0.8828 |
| 0.222         | 4.0   | 8016  | 0.4390          | 0.8917   | 0.8925    | 0.8917 | 0.8920 |
| 0.151         | 5.0   | 10020 | 0.5550          | 0.8994   | 0.8984    | 0.8994 | 0.8981 |
| 0.1544        | 6.0   | 12024 | 0.6256          | 0.9000   | 0.8995    | 0.9000 | 0.8998 |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.12.0+cu130
- Datasets 3.6.0
- Tokenizers 0.21.1