|
--- |
|
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 |
|
|
