| | --- |
| | base_model: google-bert/bert-base-multilingual-cased |
| | library_name: transformers |
| | license: apache-2.0 |
| | metrics: |
| | - accuracy |
| | - precision |
| | - recall |
| | - f1 |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: bert-f1-durga-muhammad-c |
| | 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. --> |
| |
|
| | # bert-f1-durga-muhammad-c |
| |
|
| | 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: 0.0001 |
| | - Accuracy: 1.0 |
| | - Precision: 1.0 |
| | - Recall: 1.0 |
| | - F1: 1.0 |
| |
|
| | ## 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: 24 |
| | - eval_batch_size: 24 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 1000 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:-----:| |
| | | 0.0245 | 1.0 | 42 | 0.0241 | 0.995 | 0.995 | 0.995 | 0.995 | |
| | | 0.0032 | 2.0 | 84 | 0.0081 | 0.999 | 0.999 | 0.999 | 0.999 | |
| | | 0.0011 | 3.0 | 126 | 0.0075 | 0.999 | 0.999 | 0.999 | 0.999 | |
| | | 0.0008 | 4.0 | 168 | 0.0068 | 0.999 | 0.999 | 0.999 | 0.999 | |
| | | 0.0006 | 5.0 | 210 | 0.0078 | 0.999 | 0.999 | 0.999 | 0.999 | |
| | | 0.0012 | 6.0 | 252 | 0.0063 | 0.999 | 0.999 | 0.999 | 0.999 | |
| | | 0.0022 | 7.0 | 294 | 0.0015 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | | 0.0004 | 8.0 | 336 | 0.0031 | 0.999 | 0.999 | 0.999 | 0.999 | |
| | | 0.0003 | 9.0 | 378 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | | 0.0002 | 10.0 | 420 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | | 0.0002 | 11.0 | 462 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | | 0.0002 | 12.0 | 504 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | | 0.0002 | 13.0 | 546 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | | 0.0001 | 14.0 | 588 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | | 0.0001 | 15.0 | 630 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | | 0.0001 | 16.0 | 672 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 | |
| | | 0.0001 | 17.0 | 714 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.44.2 |
| | - Pytorch 2.5.0+cu121 |
| | - Datasets 3.1.0 |
| | - Tokenizers 0.19.1 |
| |
|
