pytorch tensorboard bert question-answering dataset:persian_qa transformers generated_from_trainer model-index autotrain_compatible
---
tags:
- generated_from_trainer
datasets:
- persian_qa
model-index:
- name: bert-base-parsbert-uncased-finetuned-perQA
  results: []
---

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# bert-base-parsbert-uncased-finetuned-perQA

This model is a fine-tuned version of [HooshvareLab/bert-base-parsbert-uncased](https://huggingface.co/HooshvareLab/bert-base-parsbert-uncased) on the persian_qa dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8648

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.9599        | 1.0   | 565  | 2.0185          |
| 1.8889        | 2.0   | 1130 | 1.8088          |
| 1.4282        | 3.0   | 1695 | 1.8648          |


### Framework versions

- Transformers 4.20.0
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
