| --- |
| 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 |
| 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 |
|
|
| 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: 0.0079 |
| - Accuracy: 0.999 |
| - Precision: 0.999 |
| - Recall: 0.999 |
| - F1: 0.999 |
|
|
| ## 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: 4 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 3 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
| |:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:-----:| |
| | 0.1978 | 0.24 | 60 | 0.1764 | 0.968 | 0.968 | 0.968 | 0.968 | |
| | 0.1657 | 0.48 | 120 | 0.0619 | 0.981 | 0.981 | 0.981 | 0.981 | |
| | 0.1155 | 0.72 | 180 | 0.0475 | 0.989 | 0.989 | 0.989 | 0.989 | |
| | 0.0675 | 0.96 | 240 | 0.0143 | 0.997 | 0.997 | 0.997 | 0.997 | |
| | 0.0009 | 1.2 | 300 | 0.0148 | 0.997 | 0.997 | 0.997 | 0.997 | |
| | 0.0006 | 1.44 | 360 | 0.0151 | 0.997 | 0.997 | 0.997 | 0.997 | |
| | 0.0267 | 1.6800 | 420 | 0.0083 | 0.999 | 0.999 | 0.999 | 0.999 | |
| | 0.0335 | 1.92 | 480 | 0.0080 | 0.999 | 0.999 | 0.999 | 0.999 | |
| | 0.0315 | 2.16 | 540 | 0.0073 | 0.999 | 0.999 | 0.999 | 0.999 | |
| | 0.0056 | 2.4 | 600 | 0.0076 | 0.999 | 0.999 | 0.999 | 0.999 | |
| | 0.0004 | 2.64 | 660 | 0.0078 | 0.999 | 0.999 | 0.999 | 0.999 | |
| | 0.0004 | 2.88 | 720 | 0.0079 | 0.999 | 0.999 | 0.999 | 0.999 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.44.2 |
| - Pytorch 2.5.0+cu121 |
| - Datasets 3.0.2 |
| - Tokenizers 0.19.1 |
|
|
