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---
base_model: aubmindlab/araelectra-base-discriminator
tags:
- generated_from_trainer
datasets:
- arcd
model-index:
- name: rinna-arabert22-qa-ar2
  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. -->

# rinna-arabert22-qa-ar2

This model is a fine-tuned version of [aubmindlab/araelectra-base-discriminator](https://huggingface.co/aubmindlab/araelectra-base-discriminator) on the arcd dataset.
It achieves the following results on the evaluation set:
- Loss: 5.9506

## 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: 0.001
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 4.412         | 6.92  | 150  | 5.9506          |
| 5.9523        | 13.83 | 300  | 5.9506          |
| 5.9551        | 20.75 | 450  | 5.9506          |
| 5.952         | 27.67 | 600  | 5.9506          |
| 5.9518        | 34.58 | 750  | 5.9506          |
| 5.9501        | 41.5  | 900  | 5.9506          |
| 5.9526        | 48.41 | 1050 | 5.9506          |
| 5.9538        | 55.33 | 1200 | 5.9506          |
| 5.9517        | 62.25 | 1350 | 5.9506          |
| 5.9529        | 69.16 | 1500 | 5.9506          |
| 5.9518        | 76.08 | 1650 | 5.9506          |
| 5.9532        | 83.0  | 1800 | 5.9506          |
| 5.9518        | 89.91 | 1950 | 5.9506          |
| 5.9515        | 96.83 | 2100 | 5.9506          |


### Framework versions

- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3