metadata
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ar-poem-classification
results: []
ar-poem-classification
This model is a fine-tuned version of aubmindlab/bert-base-arabertv02 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.1427
- Macro F1: 0.6954
- Accuracy: 0.6944
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 128
- seed: 25
- gradient_accumulation_steps: 5
- total_train_batch_size: 80
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 12
Training results
Training Loss | Epoch | Step | Validation Loss | Macro F1 | Accuracy |
---|---|---|---|---|---|
No log | 1.0 | 250 | 1.0896 | 0.5319 | 0.5334 |
1.114 | 2.0 | 500 | 0.9989 | 0.5864 | 0.5826 |
1.114 | 3.0 | 750 | 0.9993 | 0.5942 | 0.5976 |
0.8219 | 4.0 | 1000 | 0.9949 | 0.6042 | 0.609 |
0.8219 | 5.0 | 1250 | 0.9813 | 0.6337 | 0.6366 |
0.563 | 6.0 | 1500 | 0.9666 | 0.6657 | 0.6654 |
0.563 | 7.0 | 1750 | 1.0253 | 0.6686 | 0.6668 |
0.3763 | 8.0 | 2000 | 1.0150 | 0.6951 | 0.6936 |
0.3763 | 9.0 | 2250 | 1.0619 | 0.6872 | 0.6872 |
0.2525 | 10.0 | 2500 | 1.1035 | 0.6929 | 0.6922 |
0.2525 | 11.0 | 2750 | 1.1352 | 0.6952 | 0.6944 |
0.184 | 12.0 | 3000 | 1.1427 | 0.6954 | 0.6944 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Tokenizers 0.15.2