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---
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
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