---
license: apache-2.0
base_model: HooshvareLab/bert-fa-base-uncased-clf-digimag
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
model-index:
- name: uncased-clf-digimag_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. -->

# uncased-clf-digimag_v1

This model is a fine-tuned version of [HooshvareLab/bert-fa-base-uncased-clf-digimag](https://huggingface.co./HooshvareLab/bert-fa-base-uncased-clf-digimag) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2679
- Accuracy: 0.6413
- F1: 0.6418
- Precision: 0.6458

## 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  | 1.1415          | 0.4972   | 0.4716 | 0.5696    |
| No log        | 2.0   | 442  | 0.9770          | 0.6016   | 0.6029 | 0.6063    |
| 1.0648        | 3.0   | 663  | 0.9529          | 0.6266   | 0.6271 | 0.6304    |
| 1.0648        | 4.0   | 884  | 0.9879          | 0.6470   | 0.6468 | 0.6636    |
| 0.6031        | 5.0   | 1105 | 1.0113          | 0.6311   | 0.6321 | 0.6345    |
| 0.6031        | 6.0   | 1326 | 1.0840          | 0.6356   | 0.6322 | 0.6363    |
| 0.329         | 7.0   | 1547 | 1.1273          | 0.6436   | 0.6438 | 0.6487    |
| 0.329         | 8.0   | 1768 | 1.2089          | 0.6300   | 0.6285 | 0.6291    |
| 0.329         | 9.0   | 1989 | 1.2486          | 0.6345   | 0.6352 | 0.6399    |
| 0.1809        | 10.0  | 2210 | 1.2679          | 0.6413   | 0.6418 | 0.6458    |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2