metadata
library_name: transformers
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert_content
results: []
bert_content
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: 1.6934
- Macro F1: 0.5805
- Macro Precision: 0.5862
- Macro Recall: 0.5892
- Accuracy: 0.5991
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: 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
Training results
| Training Loss | Epoch | Step | Validation Loss | Macro F1 | Macro Precision | Macro Recall | Accuracy |
|---|---|---|---|---|---|---|---|
| 1.2469 | 1.0 | 821 | 1.0233 | 0.5827 | 0.5896 | 0.5871 | 0.5991 |
| 0.8745 | 2.0 | 1642 | 1.0381 | 0.5912 | 0.6071 | 0.6001 | 0.6124 |
| 0.6973 | 3.0 | 2463 | 1.0917 | 0.5939 | 0.6149 | 0.6068 | 0.6191 |
| 0.4263 | 4.0 | 3284 | 1.3179 | 0.5801 | 0.5826 | 0.5951 | 0.6001 |
| 0.2791 | 5.0 | 4105 | 1.5275 | 0.5824 | 0.5921 | 0.5874 | 0.6019 |
| 0.2086 | 6.0 | 4926 | 1.6934 | 0.5805 | 0.5862 | 0.5892 | 0.5991 |
Framework versions
- Transformers 4.50.0
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.1