metadata
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: 2levels_6565
results: []
2levels_6565
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: 0.8327
- Macro F1: 0.7976
- Macro Precision: 0.8038
- Macro Recall: 0.7993
- Accuracy: 0.7982
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 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 103 | 0.4498 | 0.8015 | 0.8015 | 0.8016 | 0.8015 |
| No log | 2.0 | 206 | 0.4532 | 0.8035 | 0.8083 | 0.8049 | 0.8039 |
| No log | 3.0 | 309 | 0.5014 | 0.8066 | 0.8084 | 0.8073 | 0.8067 |
| No log | 4.0 | 412 | 0.6651 | 0.7985 | 0.8048 | 0.8002 | 0.7991 |
| 0.245 | 5.0 | 515 | 0.7793 | 0.8004 | 0.8050 | 0.8017 | 0.8008 |
| 0.245 | 6.0 | 618 | 0.8327 | 0.7976 | 0.8038 | 0.7993 | 0.7982 |
Framework versions
- Transformers 4.43.4
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.19.1