---
license: apache-2.0
base_model: sentence-transformers/LaBSE
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ternary_persian_sentiment_analysis
  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. -->

# ternary_persian_sentiment_analysis

This model is a fine-tuned version of [sentence-transformers/LaBSE](https://huggingface.co/sentence-transformers/LaBSE) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4914
- Accuracy: 0.8458
- F1 Score: 0.8459

## 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: 1e-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: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1 Score |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|
| 0.496         | 1.0   | 1394  | 0.4708          | 0.8192   | 0.8186   |
| 0.4177        | 2.0   | 2788  | 0.4914          | 0.8458   | 0.8459   |
| 0.3237        | 3.0   | 4182  | 0.5736          | 0.8354   | 0.8356   |
| 0.2874        | 4.0   | 5576  | 0.7309          | 0.8216   | 0.8217   |
| 0.2142        | 5.0   | 6970  | 0.9256          | 0.8184   | 0.8187   |
| 0.1494        | 6.0   | 8364  | 1.0608          | 0.8200   | 0.8197   |
| 0.1396        | 7.0   | 9758  | 1.0638          | 0.8257   | 0.8256   |
| 0.0983        | 8.0   | 11152 | 1.2088          | 0.8200   | 0.8200   |
| 0.0907        | 9.0   | 12546 | 1.3653          | 0.8079   | 0.8083   |
| 0.0727        | 10.0  | 13940 | 1.3032          | 0.8305   | 0.8307   |
| 0.0526        | 11.0  | 15334 | 1.4689          | 0.8184   | 0.8184   |
| 0.0413        | 12.0  | 16728 | 1.4875          | 0.8224   | 0.8227   |
| 0.0265        | 13.0  | 18122 | 1.6185          | 0.8241   | 0.8242   |
| 0.0366        | 14.0  | 19516 | 1.7135          | 0.8168   | 0.8168   |
| 0.0251        | 15.0  | 20910 | 1.6607          | 0.8249   | 0.8251   |
| 0.0151        | 16.0  | 22304 | 1.7922          | 0.8111   | 0.8111   |
| 0.0159        | 17.0  | 23698 | 1.7303          | 0.8200   | 0.8201   |
| 0.0163        | 18.0  | 25092 | 1.7555          | 0.8232   | 0.8232   |
| 0.0178        | 19.0  | 26486 | 1.7680          | 0.8232   | 0.8232   |
| 0.0147        | 20.0  | 27880 | 1.7546          | 0.8216   | 0.8217   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0