---
library_name: transformers
license: apache-2.0
base_model: HooshvareLab/bert-fa-base-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-fa-base-uncased](https://huggingface.co/HooshvareLab/bert-fa-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1790
- Accuracy: 0.8167
- F1: 0.8174

## 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   | 0.6093          | 0.7583   | 0.7592 |
| No log        | 2.0   | 136  | 0.5057          | 0.8125   | 0.8093 |
| No log        | 3.0   | 204  | 0.5610          | 0.8125   | 0.8172 |
| No log        | 4.0   | 272  | 0.7870          | 0.7958   | 0.7862 |
| No log        | 5.0   | 340  | 0.8404          | 0.8042   | 0.8105 |
| No log        | 6.0   | 408  | 0.8729          | 0.8208   | 0.8256 |
| No log        | 7.0   | 476  | 0.9832          | 0.8292   | 0.8322 |
| 0.1891        | 8.0   | 544  | 1.0597          | 0.825    | 0.8288 |
| 0.1891        | 9.0   | 612  | 1.1262          | 0.8208   | 0.8184 |
| 0.1891        | 10.0  | 680  | 1.1224          | 0.8208   | 0.8260 |
| 0.1891        | 11.0  | 748  | 1.1524          | 0.8167   | 0.8188 |
| 0.1891        | 12.0  | 816  | 1.1460          | 0.8042   | 0.8055 |
| 0.1891        | 13.0  | 884  | 1.1633          | 0.8167   | 0.8202 |
| 0.1891        | 14.0  | 952  | 1.1620          | 0.8167   | 0.8177 |
| 0.0077        | 15.0  | 1020 | 1.1790          | 0.8167   | 0.8174 |


### Framework versions

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