---
license: apache-2.0
base_model: HooshvareLab/roberta-fa-zwnj-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
model-index:
- name: roberta-fa-zwnj-base_v1
  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. -->

# roberta-fa-zwnj-base_v1

This model is a fine-tuned version of [HooshvareLab/roberta-fa-zwnj-base](https://huggingface.co/HooshvareLab/roberta-fa-zwnj-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3797
- Accuracy: 0.6288
- F1: 0.6282
- Precision: 0.6299

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|
| No log        | 1.0   | 221  | 1.1404          | 0.5176   | 0.4956 | 0.5475    |
| No log        | 2.0   | 442  | 0.9659          | 0.6163   | 0.6136 | 0.6169    |
| 1.0628        | 3.0   | 663  | 0.9516          | 0.6436   | 0.6405 | 0.6456    |
| 1.0628        | 4.0   | 884  | 0.9857          | 0.6470   | 0.6462 | 0.6530    |
| 0.6388        | 5.0   | 1105 | 1.0326          | 0.6481   | 0.6483 | 0.6490    |
| 0.6388        | 6.0   | 1326 | 1.1403          | 0.6652   | 0.6647 | 0.6664    |
| 0.3767        | 7.0   | 1547 | 1.2419          | 0.6356   | 0.6362 | 0.6383    |
| 0.3767        | 8.0   | 1768 | 1.3099          | 0.6402   | 0.6394 | 0.6398    |
| 0.3767        | 9.0   | 1989 | 1.3632          | 0.6300   | 0.6298 | 0.6297    |
| 0.2179        | 10.0  | 2210 | 1.3797          | 0.6288   | 0.6282 | 0.6299    |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2