---
license: apache-2.0
base_model: HooshvareLab/bert-fa-base-uncased-clf-persiannews
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
model-index:
- name: uncased-clf-persiannews_v1
  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. -->

# uncased-clf-persiannews_v1

This model is a fine-tuned version of [HooshvareLab/bert-fa-base-uncased-clf-persiannews](https://huggingface.co./HooshvareLab/bert-fa-base-uncased-clf-persiannews) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4385
- Accuracy: 0.6459
- F1: 0.6461
- Precision: 0.6470

## 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: 5e-06
- 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|
| No log        | 1.0   | 221  | 1.0855          | 0.6277   | 0.6263 | 0.6472    |
| No log        | 2.0   | 442  | 1.0924          | 0.6549   | 0.6545 | 0.6598    |
| 0.4554        | 3.0   | 663  | 1.1278          | 0.6583   | 0.6570 | 0.6609    |
| 0.4554        | 4.0   | 884  | 1.2085          | 0.6481   | 0.6488 | 0.6559    |
| 0.2653        | 5.0   | 1105 | 1.2614          | 0.6481   | 0.6487 | 0.6498    |
| 0.2653        | 6.0   | 1326 | 1.3392          | 0.6402   | 0.6371 | 0.6433    |
| 0.1817        | 7.0   | 1547 | 1.3692          | 0.6549   | 0.6543 | 0.6572    |
| 0.1817        | 8.0   | 1768 | 1.4216          | 0.6425   | 0.6419 | 0.6424    |
| 0.1817        | 9.0   | 1989 | 1.4325          | 0.6549   | 0.6551 | 0.6555    |
| 0.1334        | 10.0  | 2210 | 1.4385          | 0.6459   | 0.6461 | 0.6470    |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2