---
license: apache-2.0
base_model: HooshvareLab/bert-fa-base-uncased-sentiment-snappfood
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: my-snappfood-model
  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. -->

# my-snappfood-model

This model is a fine-tuned version of [HooshvareLab/bert-fa-base-uncased-sentiment-snappfood](https://huggingface.co/HooshvareLab/bert-fa-base-uncased-sentiment-snappfood) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2433
- Accuracy: 0.8613
- F1: 0.8613
- Precision: 0.8615
- Recall: 0.8613

## 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: 24
- eval_batch_size: 24
- 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     | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.2358        | 1.0   | 2363  | 0.3235          | 0.869    | 0.8690 | 0.8691    | 0.869  |
| 0.1925        | 2.0   | 4726  | 0.3717          | 0.855    | 0.8550 | 0.8553    | 0.855  |
| 0.1423        | 3.0   | 7089  | 0.5230          | 0.867    | 0.8669 | 0.8683    | 0.867  |
| 0.1135        | 4.0   | 9452  | 0.6233          | 0.8691   | 0.8690 | 0.8709    | 0.8691 |
| 0.0876        | 5.0   | 11815 | 0.7637          | 0.8636   | 0.8635 | 0.8644    | 0.8636 |
| 0.063         | 6.0   | 14178 | 0.8685          | 0.8544   | 0.8544 | 0.8547    | 0.8544 |
| 0.0435        | 7.0   | 16541 | 0.9789          | 0.8607   | 0.8606 | 0.8616    | 0.8607 |
| 0.0279        | 8.0   | 18904 | 1.1560          | 0.8579   | 0.8578 | 0.8579    | 0.8579 |
| 0.0184        | 9.0   | 21267 | 1.1904          | 0.8653   | 0.8652 | 0.8659    | 0.8653 |
| 0.0092        | 10.0  | 23630 | 1.2433          | 0.8613   | 0.8613 | 0.8615    | 0.8613 |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3