---
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_v2
  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_v2

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: 0.9489
- Accuracy: 0.6504
- F1: 0.6504
- Precision: 0.6521

## 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  | 1.1578          | 0.5051   | 0.4978 | 0.5159    |
| No log        | 2.0   | 442  | 1.0197          | 0.5846   | 0.5823 | 0.5889    |
| 1.1541        | 3.0   | 663  | 0.9553          | 0.6118   | 0.6087 | 0.6163    |
| 1.1541        | 4.0   | 884  | 0.9413          | 0.6209   | 0.6199 | 0.6281    |
| 0.8174        | 5.0   | 1105 | 0.9203          | 0.6493   | 0.6493 | 0.6506    |
| 0.8174        | 6.0   | 1326 | 0.9302          | 0.6493   | 0.6479 | 0.6551    |
| 0.6483        | 7.0   | 1547 | 0.9411          | 0.6368   | 0.6346 | 0.6379    |
| 0.6483        | 8.0   | 1768 | 0.9430          | 0.6504   | 0.6496 | 0.6514    |
| 0.6483        | 9.0   | 1989 | 0.9469          | 0.6481   | 0.6478 | 0.6500    |
| 0.5439        | 10.0  | 2210 | 0.9489          | 0.6504   | 0.6504 | 0.6521    |


### Framework versions

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