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---
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: AraElectra-finetuned-CrossVal-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-CrossVal-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: 0.5165
- Macro F1: 0.8697
- Accuracy: 0.8744
- Precision: 0.8714
- Recall: 0.8682
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|:------:|
| 0.3422 | 1.0 | 798 | 0.3336 | 0.8589 | 0.8615 | 0.8563 | 0.8652 |
| 0.216 | 2.0 | 1597 | 0.3460 | 0.8658 | 0.8714 | 0.8705 | 0.8624 |
| 0.1504 | 3.0 | 2395 | 0.5448 | 0.8485 | 0.8568 | 0.8609 | 0.8420 |
| 0.0914 | 4.0 | 3192 | 0.5165 | 0.8697 | 0.8744 | 0.8714 | 0.8682 |
### Framework versions
- Transformers 4.27.4
- Pytorch 1.13.0
- Datasets 2.1.0
- Tokenizers 0.13.2
|