|
--- |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
- precision |
|
- recall |
|
model-index: |
|
- name: AraElectra-finetuned-fnd |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# AraElectra-finetuned-fnd |
|
|
|
This model is a fine-tuned version of [aubmindlab/araelectra-base-discriminator](https://huggingface.co/aubmindlab/araelectra-base-discriminator) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.6073 |
|
- Macro F1: 0.7629 |
|
- Accuracy: 0.7708 |
|
- Precision: 0.7646 |
|
- Recall: 0.7616 |
|
|
|
## 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: 8 |
|
- seed: 25 |
|
- 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|:------:| |
|
| 0.5248 | 1.0 | 1597 | 0.4960 | 0.7416 | 0.7546 | 0.7508 | 0.7377 | |
|
| 0.4308 | 2.0 | 3194 | 0.4770 | 0.7535 | 0.7666 | 0.7647 | 0.7490 | |
|
| 0.3386 | 3.0 | 4791 | 0.5201 | 0.7614 | 0.7684 | 0.7617 | 0.7611 | |
|
| 0.2781 | 4.0 | 6388 | 0.6073 | 0.7629 | 0.7708 | 0.7646 | 0.7616 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.27.4 |
|
- Pytorch 1.13.0 |
|
- Datasets 2.1.0 |
|
- Tokenizers 0.13.2 |
|
|
