---
library_name: transformers
license: apache-2.0
base_model: rezaFarsh/ternary_persian_sentiment_analysis
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 [rezaFarsh/ternary_persian_sentiment_analysis](https://huggingface.co./rezaFarsh/ternary_persian_sentiment_analysis) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2467
- Accuracy: 0.3696
- F1: 0.2679

## 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   | 3.0226          | 0.1739   | 0.1632 |
| No log        | 2.0   | 52   | 2.0593          | 0.3261   | 0.2614 |
| No log        | 3.0   | 78   | 1.6844          | 0.3696   | 0.2821 |
| No log        | 4.0   | 104  | 1.4833          | 0.3696   | 0.2731 |
| No log        | 5.0   | 130  | 1.3616          | 0.3913   | 0.2871 |
| No log        | 6.0   | 156  | 1.3051          | 0.3913   | 0.2871 |
| No log        | 7.0   | 182  | 1.2747          | 0.3913   | 0.2871 |
| No log        | 8.0   | 208  | 1.2585          | 0.3696   | 0.2679 |
| No log        | 9.0   | 234  | 1.2488          | 0.3913   | 0.2871 |
| No log        | 10.0  | 260  | 1.2467          | 0.3696   | 0.2679 |


### Framework versions

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