| | --- |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - precision |
| | - recall |
| | - f1 |
| | model-index: |
| | - name: M12-BERT-SIMILIARITY |
| | 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. --> |
| |
|
| | # M12-BERT-SIMILIARITY |
| |
|
| | This model is a fine-tuned version of [aubmindlab/bert-base-arabertv2](https://huggingface.co/aubmindlab/bert-base-arabertv2) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.2225 |
| | - Accuracy: 0.9344 |
| | - Precision: 0.8927 |
| | - Recall: 0.9873 |
| | - F1: 0.9377 |
| |
|
| | ## 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 | |
| | |:-------------:|:-----:|:------:|:---------------:|:--------:|:---------:|:------:|:------:| |
| | | 0.2303 | 1.0 | 49975 | 0.2080 | 0.9372 | 0.9036 | 0.9787 | 0.9397 | |
| | | 0.2109 | 2.0 | 99950 | 0.2342 | 0.9337 | 0.8952 | 0.9825 | 0.9368 | |
| | | 0.203 | 3.0 | 149925 | 0.2192 | 0.9375 | 0.9070 | 0.9749 | 0.9397 | |
| | | 0.1962 | 4.0 | 199900 | 0.2225 | 0.9344 | 0.8927 | 0.9873 | 0.9377 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.21.3 |
| | - Pytorch 1.12.1+cu113 |
| | - Datasets 2.4.0 |
| | - Tokenizers 0.12.1 |
| |
|
