---
library_name: transformers
license: apache-2.0
base_model: HooshvareLab/bert-fa-base-uncased
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 [HooshvareLab/bert-fa-base-uncased](https://huggingface.co/HooshvareLab/bert-fa-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0154
- Accuracy: 0.8333
- F1: 0.8456

## 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: 5e-06
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 68   | 0.5588          | 0.8333   | 0.8419 |
| No log        | 2.0   | 136  | 0.5678          | 0.8417   | 0.8557 |
| No log        | 3.0   | 204  | 0.6083          | 0.8208   | 0.8311 |
| No log        | 4.0   | 272  | 0.6749          | 0.8167   | 0.8285 |
| No log        | 5.0   | 340  | 0.7690          | 0.8292   | 0.8424 |
| No log        | 6.0   | 408  | 0.8706          | 0.8208   | 0.8328 |
| No log        | 7.0   | 476  | 0.8554          | 0.8292   | 0.8424 |
| 0.0725        | 8.0   | 544  | 0.8950          | 0.825    | 0.8390 |
| 0.0725        | 9.0   | 612  | 0.9200          | 0.825    | 0.8390 |
| 0.0725        | 10.0  | 680  | 0.9511          | 0.8292   | 0.8455 |
| 0.0725        | 11.0  | 748  | 0.9698          | 0.8375   | 0.8490 |
| 0.0725        | 12.0  | 816  | 0.9829          | 0.8333   | 0.8456 |
| 0.0725        | 13.0  | 884  | 1.0022          | 0.8333   | 0.8456 |
| 0.0725        | 14.0  | 952  | 1.0130          | 0.8333   | 0.8456 |
| 0.0167        | 15.0  | 1020 | 1.0154          | 0.8333   | 0.8456 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1