---
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: 0.5224
- Accuracy: 0.8
- F1: 0.7972

## 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   | 135  | 0.7296          | 0.7292   | 0.6649 |
| No log        | 2.0   | 270  | 0.6285          | 0.7875   | 0.7794 |
| No log        | 3.0   | 405  | 0.5707          | 0.8      | 0.7931 |
| 0.6461        | 4.0   | 540  | 0.5545          | 0.8      | 0.7936 |
| 0.6461        | 5.0   | 675  | 0.5248          | 0.8125   | 0.8080 |
| 0.6461        | 6.0   | 810  | 0.5166          | 0.8042   | 0.8001 |
| 0.6461        | 7.0   | 945  | 0.5170          | 0.8042   | 0.8093 |
| 0.3513        | 8.0   | 1080 | 0.5179          | 0.8042   | 0.8064 |
| 0.3513        | 9.0   | 1215 | 0.5212          | 0.8      | 0.8006 |
| 0.3513        | 10.0  | 1350 | 0.5224          | 0.8      | 0.7972 |


### Framework versions

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