---
license: apache-2.0
base_model: dadashzadeh/tiny-bert-Sentiment-persian
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: tiny-bert-Sentiment-persian
  results: []
datasets:
- hezarai/sentiment-dksf
language:
- fa
pipeline_tag: text-classification
---

<!-- 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. -->

# tiny-bert-Sentiment-persian

This model is a fine-tuned version of [dadashzadeh/tiny-bert-Sentiment-persian](https://huggingface.co/dadashzadeh/tiny-bert-Sentiment-persian) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6553
- Accuracy: 0.7611

## 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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 45
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 12
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Accuracy |
|:-------------:|:-------:|:-----:|:---------------:|:--------:|
| 0.6157        | 0.9999  | 3575  | 0.6703          | 0.7577   |
| 0.5833        | 1.9999  | 7150  | 0.7599          | 0.7171   |
| 0.6015        | 2.9998  | 10725 | 0.6824          | 0.7590   |
| 0.5601        | 4.0     | 14301 | 0.6780          | 0.7533   |
| 0.5699        | 4.9999  | 17876 | 0.7071          | 0.7356   |
| 0.5519        | 5.9999  | 21451 | 0.6931          | 0.7391   |
| 0.5436        | 6.9998  | 25026 | 0.6736          | 0.7629   |
| 0.5482        | 8.0     | 28602 | 0.6567          | 0.7685   |
| 0.5367        | 8.9999  | 32177 | 0.6553          | 0.7611   |
| 0.5399        | 9.9999  | 35752 | 0.6691          | 0.7616   |
| 0.5112        | 10.9998 | 39327 | 0.6785          | 0.7564   |
| 0.5113        | 11.9992 | 42900 | 0.6773          | 0.7572   |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.2+cu118
- Datasets 2.19.1
- Tokenizers 0.19.1