---
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: 1.0549
- Accuracy: 0.4130
- F1: 0.2905

## 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-06
- train_batch_size: 16
- eval_batch_size: 64
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 26   | 1.0480          | 0.4130   | 0.2522 |
| No log        | 2.0   | 52   | 1.0572          | 0.4130   | 0.2522 |
| No log        | 3.0   | 78   | 1.0568          | 0.3913   | 0.2232 |
| No log        | 4.0   | 104  | 1.0601          | 0.3913   | 0.2418 |
| No log        | 5.0   | 130  | 1.0565          | 0.3913   | 0.2566 |
| No log        | 6.0   | 156  | 1.0561          | 0.3913   | 0.2684 |
| No log        | 7.0   | 182  | 1.0562          | 0.4130   | 0.2905 |
| No log        | 8.0   | 208  | 1.0557          | 0.3913   | 0.2684 |
| No log        | 9.0   | 234  | 1.0550          | 0.4130   | 0.2905 |
| No log        | 10.0  | 260  | 1.0549          | 0.4130   | 0.2905 |


### Framework versions

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