2levels_52521
This model is a fine-tuned version of aubmindlab/bert-base-arabertv02 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9976
- Macro F1: 0.8132
- Macro Precision: 0.8220
- Macro Recall: 0.8153
- Accuracy: 0.8140
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: 64
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
Training results
Training Loss | Epoch | Step | Validation Loss | Macro F1 | Macro Precision | Macro Recall | Accuracy |
---|---|---|---|---|---|---|---|
0.4301 | 1.0 | 821 | 0.3758 | 0.8300 | 0.8360 | 0.8315 | 0.8305 |
0.2994 | 2.0 | 1642 | 0.4510 | 0.8141 | 0.8311 | 0.8175 | 0.8157 |
0.2131 | 3.0 | 2463 | 0.5463 | 0.8077 | 0.8252 | 0.8113 | 0.8095 |
0.0958 | 4.0 | 3284 | 0.7365 | 0.8081 | 0.8229 | 0.8113 | 0.8096 |
0.055 | 5.0 | 4105 | 0.9349 | 0.8113 | 0.8245 | 0.8142 | 0.8126 |
0.0352 | 6.0 | 4926 | 0.9976 | 0.8132 | 0.8220 | 0.8153 | 0.8140 |
Framework versions
- Transformers 4.43.4
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.19.1
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Model tree for Noorrabie/2levels_52521
Base model
aubmindlab/bert-base-arabertv02