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---
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: 1.0798
- Accuracy: 0.5652
- F1: 0.5901
## 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: 3e-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: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log | 1.0 | 52 | 1.0320 | 0.4130 | 0.2269 |
| No log | 2.0 | 104 | 0.9651 | 0.4783 | 0.4406 |
| No log | 3.0 | 156 | 1.0128 | 0.5435 | 0.5541 |
| No log | 4.0 | 208 | 1.0869 | 0.5870 | 0.6025 |
| No log | 5.0 | 260 | 1.0798 | 0.5652 | 0.5901 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
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