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---
license: apache-2.0
base_model: google-bert/bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: pii_mbert_az
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. -->
# pii_mbert_az
This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1319
- Precision: 0.8726
- Recall: 0.9026
- F1: 0.8874
- Accuracy: 0.9619
## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: reduce_lr_on_plateau
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 313 | 0.1464 | 0.8797 | 0.8615 | 0.8705 | 0.9587 |
| 0.2128 | 2.0 | 626 | 0.1319 | 0.8726 | 0.9026 | 0.8874 | 0.9619 |
| 0.2128 | 3.0 | 939 | 0.1461 | 0.8689 | 0.8924 | 0.8805 | 0.9596 |
| 0.0783 | 4.0 | 1252 | 0.1529 | 0.8837 | 0.9049 | 0.8942 | 0.9620 |
| 0.0443 | 5.0 | 1565 | 0.1921 | 0.8657 | 0.9157 | 0.8900 | 0.9615 |
| 0.0443 | 6.0 | 1878 | 0.1647 | 0.8975 | 0.9224 | 0.9098 | 0.9685 |
| 0.0201 | 7.0 | 2191 | 0.1725 | 0.8904 | 0.9183 | 0.9041 | 0.9674 |
| 0.0098 | 8.0 | 2504 | 0.1766 | 0.8917 | 0.9199 | 0.9056 | 0.9682 |
| 0.0098 | 9.0 | 2817 | 0.1756 | 0.8926 | 0.9202 | 0.9062 | 0.9686 |
| 0.007 | 10.0 | 3130 | 0.1763 | 0.8916 | 0.9189 | 0.9051 | 0.9684 |
| 0.007 | 11.0 | 3443 | 0.1772 | 0.8907 | 0.9183 | 0.9043 | 0.9682 |
| 0.007 | 12.0 | 3756 | 0.1773 | 0.8895 | 0.9173 | 0.9032 | 0.9680 |
| 0.0067 | 13.0 | 4069 | 0.1775 | 0.8892 | 0.9170 | 0.9029 | 0.9680 |
| 0.0067 | 14.0 | 4382 | 0.1775 | 0.8897 | 0.9170 | 0.9032 | 0.9679 |
| 0.0062 | 15.0 | 4695 | 0.1775 | 0.8897 | 0.9170 | 0.9032 | 0.9679 |
### Framework versions
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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