| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - precision |
| - recall |
| - f1 |
| model-index: |
| - name: fine-tuned-bert-base-multilingual-uncased-NED_latest |
| 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. --> |
|
|
| # fine-tuned-bert-base-multilingual-uncased-NED_latest |
| |
| This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.1376 |
| - Accuracy: 0.9687 |
| - Precision: 0.9761 |
| - Recall: 0.9764 |
| - F1: 0.9762 |
| |
| ## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 10 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
| |:-------------:|:-----:|:------:|:---------------:|:--------:|:---------:|:------:|:------:| |
| | 0.157 | 1.0 | 56232 | 0.1271 | 0.9658 | 0.9740 | 0.9741 | 0.9740 | |
| | 0.144 | 2.0 | 112464 | 0.1549 | 0.9665 | 0.9693 | 0.9802 | 0.9747 | |
| | 0.1439 | 3.0 | 168696 | 0.1600 | 0.9660 | 0.9701 | 0.9786 | 0.9743 | |
| | 0.1267 | 4.0 | 224928 | 0.1376 | 0.9687 | 0.9761 | 0.9764 | 0.9762 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.19.2 |
| - Pytorch 1.11.0+cu113 |
| - Datasets 2.2.2 |
| - Tokenizers 0.12.1 |
| |
