---
base_model: HooshvareLab/bert-base-parsbert-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
model-index:
- name: Persian-Text-Sentiment-Bert-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. -->

# Persian-Text-Sentiment-Bert-V1

This model is a fine-tuned version of [HooshvareLab/bert-base-parsbert-uncased](https://huggingface.co/HooshvareLab/bert-base-parsbert-uncased) on a custom dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3265
- Precision: 0.8727
- Recall: 0.8716
- F1-score: 0.8715
- Accuracy: 0.8716

## 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: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1-score | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:--------:|:--------:|
| 0.3097        | 1.0   | 3491  | 0.3265          | 0.8727    | 0.8716 | 0.8715   | 0.8716   |
| 0.2686        | 2.0   | 6982  | 0.3602          | 0.8785    | 0.8758 | 0.8756   | 0.8758   |
| 0.2137        | 3.0   | 10473 | 0.3828          | 0.8759    | 0.8724 | 0.8721   | 0.8724   |
| 0.1823        | 4.0   | 13964 | 0.5545          | 0.8637    | 0.8636 | 0.8636   | 0.8636   |
| 0.1346        | 5.0   | 17455 | 0.6295          | 0.8572    | 0.8566 | 0.8566   | 0.8566   |
| 0.1001        | 6.0   | 20946 | 0.8501          | 0.8606    | 0.8604 | 0.8604   | 0.8604   |
| 0.071         | 7.0   | 24437 | 1.0192          | 0.8596    | 0.8594 | 0.8594   | 0.8594   |
| 0.0604        | 8.0   | 27928 | 1.0449          | 0.8553    | 0.8553 | 0.8553   | 0.8553   |
| 0.0312        | 9.0   | 31419 | 1.1677          | 0.8598    | 0.8598 | 0.8598   | 0.8598   |
| 0.022         | 10.0  | 34910 | 1.2128          | 0.8593    | 0.8591 | 0.8591   | 0.8591   |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3