---
license: apache-2.0
base_model: google-bert/bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: absa-train-service-gg-bert-multilingual
  results: []
---

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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/cunho2803032003/absa-1721788682.8055813/runs/6du7w59h)
# absa-train-service-gg-bert-multilingual

This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9467
- Accuracy: 0.4667
- Precision: 0.4925
- Recall: 0.4772
- F1: 0.4218

## 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: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 2.2865        | 1.0   | 438  | 2.2450          | 0.2067   | 0.1363    | 0.2097 | 0.1125 |
| 2.2026        | 2.0   | 876  | 2.1433          | 0.3013   | 0.3069    | 0.3118 | 0.2477 |
| 2.1325        | 3.0   | 1314 | 2.0787          | 0.3307   | 0.4191    | 0.3267 | 0.2936 |
| 2.0705        | 4.0   | 1752 | 2.0219          | 0.4107   | 0.4532    | 0.4202 | 0.3533 |
| 2.0617        | 5.0   | 2190 | 1.9910          | 0.4293   | 0.3812    | 0.4402 | 0.3826 |
| 2.0226        | 6.0   | 2628 | 1.9646          | 0.4333   | 0.4792    | 0.4421 | 0.3745 |
| 1.9997        | 7.0   | 3066 | 1.9522          | 0.4733   | 0.5002    | 0.4838 | 0.4294 |
| 1.9882        | 8.0   | 3504 | 1.9467          | 0.4667   | 0.4925    | 0.4772 | 0.4218 |


### Framework versions

- Transformers 4.43.1
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1