---
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: 1.0798
- Accuracy: 0.5652
- F1: 0.5901

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 52   | 1.0320          | 0.4130   | 0.2269 |
| No log        | 2.0   | 104  | 0.9651          | 0.4783   | 0.4406 |
| No log        | 3.0   | 156  | 1.0128          | 0.5435   | 0.5541 |
| No log        | 4.0   | 208  | 1.0869          | 0.5870   | 0.6025 |
| No log        | 5.0   | 260  | 1.0798          | 0.5652   | 0.5901 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1