---
license: apache-2.0
base_model: makhataei/qa-persian-bert-fa-base-uncased
tags:
- generated_from_trainer
model-index:
- name: qa-persian-bert-fa-base-uncased
  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. -->

# qa-persian-bert-fa-base-uncased

This model is a fine-tuned version of [makhataei/qa-persian-bert-fa-base-uncased](https://huggingface.co/makhataei/qa-persian-bert-fa-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 5.3355

## 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: 1.5625e-09
- train_batch_size: 14
- eval_batch_size: 14
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 5.5993        | 1.0   | 9    | 5.3355          |
| 5.6986        | 2.0   | 18   | 5.3355          |
| 5.6845        | 3.0   | 27   | 5.3355          |
| 5.6475        | 4.0   | 36   | 5.3355          |
| 5.7219        | 5.0   | 45   | 5.3355          |
| 5.6464        | 6.0   | 54   | 5.3355          |
| 5.5938        | 7.0   | 63   | 5.3355          |
| 5.577         | 8.0   | 72   | 5.3355          |
| 5.5841        | 9.0   | 81   | 5.3355          |
| 5.5863        | 10.0  | 90   | 5.3355          |
| 5.5771        | 11.0  | 99   | 5.3355          |
| 5.6131        | 12.0  | 108  | 5.3355          |
| 5.6692        | 13.0  | 117  | 5.3355          |
| 5.7031        | 14.0  | 126  | 5.3355          |
| 5.6995        | 15.0  | 135  | 5.3355          |
| 5.6724        | 16.0  | 144  | 5.3355          |
| 5.7379        | 17.0  | 153  | 5.3355          |
| 5.6687        | 18.0  | 162  | 5.3355          |
| 5.7009        | 19.0  | 171  | 5.3355          |
| 5.6232        | 20.0  | 180  | 5.3355          |
| 5.6514        | 21.0  | 189  | 5.3355          |
| 5.6814        | 22.0  | 198  | 5.3355          |
| 5.6305        | 23.0  | 207  | 5.3355          |
| 5.7508        | 24.0  | 216  | 5.3355          |
| 5.6747        | 25.0  | 225  | 5.3355          |
| 5.6642        | 26.0  | 234  | 5.3355          |
| 5.6913        | 27.0  | 243  | 5.3355          |
| 5.673         | 28.0  | 252  | 5.3355          |
| 5.6222        | 29.0  | 261  | 5.3355          |
| 5.6194        | 30.0  | 270  | 5.3355          |
| 5.6944        | 31.0  | 279  | 5.3355          |
| 5.6899        | 32.0  | 288  | 5.3355          |
| 5.6165        | 33.0  | 297  | 5.3355          |
| 5.6643        | 34.0  | 306  | 5.3355          |
| 5.7039        | 35.0  | 315  | 5.3355          |
| 5.6704        | 36.0  | 324  | 5.3355          |
| 5.694         | 37.0  | 333  | 5.3355          |
| 5.6058        | 38.0  | 342  | 5.3355          |
| 5.5774        | 39.0  | 351  | 5.3355          |
| 5.5987        | 40.0  | 360  | 5.3355          |
| 5.6706        | 41.0  | 369  | 5.3355          |
| 5.644         | 42.0  | 378  | 5.3355          |
| 5.6432        | 43.0  | 387  | 5.3355          |
| 5.6055        | 44.0  | 396  | 5.3355          |
| 5.6086        | 45.0  | 405  | 5.3355          |
| 5.738         | 46.0  | 414  | 5.3355          |
| 5.6526        | 47.0  | 423  | 5.3355          |
| 5.6566        | 48.0  | 432  | 5.3355          |
| 5.6381        | 49.0  | 441  | 5.3355          |
| 5.7056        | 50.0  | 450  | 5.3355          |
| 5.6693        | 51.0  | 459  | 5.3355          |
| 5.6042        | 52.0  | 468  | 5.3355          |
| 5.6551        | 53.0  | 477  | 5.3355          |
| 5.5851        | 54.0  | 486  | 5.3355          |
| 5.6209        | 55.0  | 495  | 5.3355          |
| 5.6143        | 56.0  | 504  | 5.3355          |
| 5.6426        | 57.0  | 513  | 5.3355          |
| 5.589         | 58.0  | 522  | 5.3355          |
| 5.6143        | 59.0  | 531  | 5.3355          |
| 5.6736        | 60.0  | 540  | 5.3355          |
| 5.6754        | 61.0  | 549  | 5.3355          |
| 5.6884        | 62.0  | 558  | 5.3355          |
| 5.677         | 63.0  | 567  | 5.3355          |
| 5.6157        | 64.0  | 576  | 5.3355          |
| 5.618         | 65.0  | 585  | 5.3355          |
| 5.678         | 66.0  | 594  | 5.3355          |
| 5.6859        | 67.0  | 603  | 5.3355          |
| 5.6751        | 68.0  | 612  | 5.3355          |
| 5.5911        | 69.0  | 621  | 5.3355          |
| 5.66          | 70.0  | 630  | 5.3355          |
| 5.7322        | 71.0  | 639  | 5.3355          |
| 5.6169        | 72.0  | 648  | 5.3355          |
| 5.6718        | 73.0  | 657  | 5.3355          |
| 5.6933        | 74.0  | 666  | 5.3355          |
| 5.5852        | 75.0  | 675  | 5.3355          |
| 5.5871        | 76.0  | 684  | 5.3355          |
| 5.6518        | 77.0  | 693  | 5.3355          |
| 5.6022        | 78.0  | 702  | 5.3355          |
| 5.6427        | 79.0  | 711  | 5.3355          |
| 5.639         | 80.0  | 720  | 5.3355          |
| 5.6559        | 81.0  | 729  | 5.3355          |
| 5.6959        | 82.0  | 738  | 5.3355          |
| 5.6081        | 83.0  | 747  | 5.3355          |
| 5.6185        | 84.0  | 756  | 5.3355          |
| 5.638         | 85.0  | 765  | 5.3355          |
| 5.6206        | 86.0  | 774  | 5.3355          |
| 5.7414        | 87.0  | 783  | 5.3355          |
| 5.7041        | 88.0  | 792  | 5.3355          |
| 5.6389        | 89.0  | 801  | 5.3355          |
| 5.6339        | 90.0  | 810  | 5.3355          |
| 5.6446        | 91.0  | 819  | 5.3355          |
| 5.6303        | 92.0  | 828  | 5.3355          |
| 5.6814        | 93.0  | 837  | 5.3355          |
| 5.6435        | 94.0  | 846  | 5.3355          |
| 5.6822        | 95.0  | 855  | 5.3355          |
| 5.6318        | 96.0  | 864  | 5.3355          |
| 5.6404        | 97.0  | 873  | 5.3355          |
| 5.6277        | 98.0  | 882  | 5.3355          |
| 5.639         | 99.0  | 891  | 5.3355          |
| 5.6655        | 100.0 | 900  | 5.3355          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.0.1+cu117
- Datasets 2.15.0
- Tokenizers 0.15.0