---
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: 0.4345
- Accuracy: 0.8627
- F1: 0.8098

## 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   | 143  | 0.6861          | 0.7412   | 0.6297 |
| No log        | 2.0   | 286  | 0.4557          | 0.8510   | 0.7951 |
| No log        | 3.0   | 429  | 0.3941          | 0.8627   | 0.8116 |
| 0.5612        | 4.0   | 572  | 0.3894          | 0.8627   | 0.8081 |
| 0.5612        | 5.0   | 715  | 0.4092          | 0.8588   | 0.8071 |
| 0.5612        | 6.0   | 858  | 0.3987          | 0.8627   | 0.8077 |
| 0.2275        | 7.0   | 1001 | 0.4105          | 0.8784   | 0.8264 |
| 0.2275        | 8.0   | 1144 | 0.4192          | 0.8627   | 0.8071 |
| 0.2275        | 9.0   | 1287 | 0.4305          | 0.8667   | 0.8113 |
| 0.2275        | 10.0  | 1430 | 0.4345          | 0.8627   | 0.8098 |


### Framework versions

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