metadata
library_name: transformers
base_model: aubmindlab/bert-large-arabertv02
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: EOS_bert
results: []
EOS_bert
This model is a fine-tuned version of aubmindlab/bert-large-arabertv02 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0007
- Accuracy: 1.0
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: 16
- seed: 42
- optimizer: Use 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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 57 | 0.5427 | 0.81 |
| No log | 2.0 | 114 | 0.3237 | 0.91 |
| No log | 3.0 | 171 | 0.1998 | 0.97 |
| No log | 4.0 | 228 | 0.0504 | 1.0 |
| No log | 5.0 | 285 | 0.0290 | 1.0 |
| No log | 6.0 | 342 | 0.0033 | 1.0 |
| No log | 7.0 | 399 | 0.0026 | 1.0 |
| No log | 8.0 | 456 | 0.0009 | 1.0 |
| 0.2254 | 9.0 | 513 | 0.0007 | 1.0 |
| 0.2254 | 10.0 | 570 | 0.0007 | 1.0 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3