---
library_name: transformers
license: apache-2.0
base_model: dadashzadeh/roberta-sentiment-persian
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 [dadashzadeh/roberta-sentiment-persian](https://huggingface.co/dadashzadeh/roberta-sentiment-persian) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3240
- Accuracy: 0.8375
- F1: 0.8225

## 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: 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 270  | 0.6400          | 0.8292   | 0.8140 |
| 0.256         | 2.0   | 540  | 0.8620          | 0.8083   | 0.7919 |
| 0.256         | 3.0   | 810  | 0.9867          | 0.8375   | 0.8239 |
| 0.1045        | 4.0   | 1080 | 1.0124          | 0.8375   | 0.8213 |
| 0.1045        | 5.0   | 1350 | 1.0423          | 0.825    | 0.8135 |
| 0.0397        | 6.0   | 1620 | 1.3452          | 0.8292   | 0.8136 |
| 0.0397        | 7.0   | 1890 | 1.1964          | 0.8333   | 0.8192 |
| 0.0119        | 8.0   | 2160 | 1.3196          | 0.8292   | 0.8140 |
| 0.0119        | 9.0   | 2430 | 1.3148          | 0.8292   | 0.8138 |
| 0.0043        | 10.0  | 2700 | 1.3240          | 0.8375   | 0.8225 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1