metadata
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: AraElectra-finetuned-CrossVal-fnd
results: []
AraElectra-finetuned-CrossVal-fnd
This model is a fine-tuned version of aubmindlab/araelectra-base-discriminator on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1317
- Macro F1: 0.9489
- Accuracy: 0.9505
- Precision: 0.9488
- Recall: 0.9490
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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 123
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Macro F1 | Accuracy | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.3788 | 1.0 | 798 | 0.1687 | 0.9453 | 0.9473 | 0.9480 | 0.9431 |
| 0.2273 | 2.0 | 1597 | 0.1876 | 0.9200 | 0.9239 | 0.9306 | 0.9134 |
| 0.1611 | 3.0 | 2395 | 0.1317 | 0.9489 | 0.9505 | 0.9488 | 0.9490 |
| 0.0972 | 4.0 | 3192 | 0.1685 | 0.9484 | 0.9501 | 0.9489 | 0.9479 |
Framework versions
- Transformers 4.27.4
- Pytorch 1.13.0
- Datasets 2.1.0
- Tokenizers 0.13.2