---
library_name: transformers
base_model: HooshvareLab/bert-base-parsbert-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: Bert-Sentiment-Fa
  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. -->

# Bert-Sentiment-Fa

This model is a fine-tuned version of [HooshvareLab/bert-base-parsbert-uncased](https://huggingface.co/HooshvareLab/bert-base-parsbert-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1461
- Accuracy: 0.8208
- F1: 0.8230

## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 68   | 0.4975          | 0.7917   | 0.7896 |
| No log        | 2.0   | 136  | 0.5646          | 0.8125   | 0.8163 |
| No log        | 3.0   | 204  | 0.6853          | 0.8167   | 0.8072 |
| No log        | 4.0   | 272  | 0.9142          | 0.8      | 0.7987 |
| No log        | 5.0   | 340  | 0.8389          | 0.8375   | 0.8393 |
| No log        | 6.0   | 408  | 0.8732          | 0.8208   | 0.8148 |
| No log        | 7.0   | 476  | 0.9233          | 0.825    | 0.8226 |
| 0.1198        | 8.0   | 544  | 0.9971          | 0.8042   | 0.7896 |
| 0.1198        | 9.0   | 612  | 1.0807          | 0.8167   | 0.8154 |
| 0.1198        | 10.0  | 680  | 1.0949          | 0.825    | 0.8242 |
| 0.1198        | 11.0  | 748  | 1.0613          | 0.8083   | 0.8098 |
| 0.1198        | 12.0  | 816  | 1.0842          | 0.8083   | 0.8095 |
| 0.1198        | 13.0  | 884  | 1.1327          | 0.8167   | 0.8195 |
| 0.1198        | 14.0  | 952  | 1.1332          | 0.8125   | 0.8130 |
| 0.0073        | 15.0  | 1020 | 1.1461          | 0.8208   | 0.8230 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1