metadata
library_name: transformers
base_model: aubmindlab/bert-base-arabertv2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-base-arabertv2_D3Lex_CE_19levels
results: []
bert-base-arabertv2_D3Lex_CE_19levels
This model is a fine-tuned version of aubmindlab/bert-base-arabertv2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.8342
- Macro F1: 0.4364
- Macro Precision: 0.4424
- Macro Recall: 0.4454
- Accuracy: 0.5140
- Accuracy With Margin: 0.6744
- Distance: 1.2527
- Quadratic weighted kappa: 0.7889
- Accuracy 7: 0.6179
- Accuracy 5: 0.6653
- Accuracy 3: 0.7363
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 6
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Macro F1 | Macro Precision | Macro Recall | Accuracy | Accuracy With Margin | Distance | Quadratic weighted kappa | Accuracy 7 | Accuracy 5 | Accuracy 3 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1.8254 | 1.0 | 857 | 1.4573 | 0.3478 | 0.3741 | 0.3804 | 0.5044 | 0.6513 | 1.3171 | 0.7790 | 0.6223 | 0.6773 | 0.7415 |
| 1.2699 | 2.0 | 1714 | 1.4409 | 0.4133 | 0.4330 | 0.4316 | 0.5157 | 0.6688 | 1.2666 | 0.7825 | 0.6230 | 0.6802 | 0.7497 |
| 1.0213 | 3.0 | 2571 | 1.4714 | 0.4157 | 0.4210 | 0.4276 | 0.5272 | 0.6711 | 1.2473 | 0.7889 | 0.6308 | 0.6780 | 0.7458 |
| 0.8308 | 4.0 | 3428 | 1.6169 | 0.4074 | 0.4422 | 0.4110 | 0.5171 | 0.6724 | 1.2573 | 0.7848 | 0.6194 | 0.6663 | 0.7397 |
| 0.6128 | 5.0 | 4285 | 1.7657 | 0.4222 | 0.4375 | 0.4349 | 0.5164 | 0.6737 | 1.2575 | 0.7861 | 0.6208 | 0.6703 | 0.7391 |
| 0.4786 | 6.0 | 5142 | 1.8342 | 0.4364 | 0.4424 | 0.4454 | 0.5140 | 0.6744 | 1.2527 | 0.7889 | 0.6179 | 0.6653 | 0.7363 |
Framework versions
- Transformers 4.53.2
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.2