metadata
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert_13_levels
results: []
bert_13_levels
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: 1.3439
- Macro F1: 0.5121
- Macro Precision: 0.4957
- Macro Recall: 0.5371
- Accuracy: 0.6763
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 |
|---|---|---|---|---|---|---|---|
| 1.1416 | 1.0 | 821 | 0.8787 | 0.5043 | 0.4933 | 0.5272 | 0.6984 |
| 0.7613 | 2.0 | 1642 | 0.8876 | 0.5004 | 0.5194 | 0.5160 | 0.6938 |
| 0.6042 | 3.0 | 2463 | 0.9361 | 0.5274 | 0.5010 | 0.5652 | 0.6936 |
| 0.3808 | 4.0 | 3284 | 1.0780 | 0.5251 | 0.5128 | 0.5523 | 0.6847 |
| 0.2474 | 5.0 | 4105 | 1.2235 | 0.5181 | 0.4991 | 0.5468 | 0.6858 |
| 0.1856 | 6.0 | 4926 | 1.3439 | 0.5121 | 0.4957 | 0.5371 | 0.6763 |
Framework versions
- Transformers 4.43.4
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.19.1