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bert-fa-base-uncased-finetuned-ParsBert
This repo is just a try to learn working with hugging face. This model is a fine-tuned version of HooshvareLab/bert-fa-base-uncased on a very simple handmade dataset from !kaggle datasets download -d miladfa7/persian-wikipedia-dataset. It achieves the following results on the evaluation set:
- Loss: 1.8240 https://colab.research.google.com/drive/1gqE1AHdEDl20QNC5lF548-5NQujjp9zU?usp=sharing
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 8 | 2.0729 |
| No log | 2.0 | 16 | 1.9354 |
| No log | 3.0 | 24 | 2.0527 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
