---
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_v2
  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_v2

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: 1.2940
- Accuracy: 0.6481
- F1: 0.6482
- Precision: 0.6531

## 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  | 1.1060          | 0.5199   | 0.4953 | 0.5440    |
| No log        | 2.0   | 442  | 0.9657          | 0.6220   | 0.6234 | 0.6304    |
| 1.0805        | 3.0   | 663  | 0.9398          | 0.6583   | 0.6591 | 0.6626    |
| 1.0805        | 4.0   | 884  | 0.9883          | 0.6504   | 0.6511 | 0.6710    |
| 0.6186        | 5.0   | 1105 | 1.0283          | 0.6459   | 0.6456 | 0.6506    |
| 0.6186        | 6.0   | 1326 | 1.1060          | 0.6527   | 0.6503 | 0.6602    |
| 0.3377        | 7.0   | 1547 | 1.1505          | 0.6652   | 0.6642 | 0.6786    |
| 0.3377        | 8.0   | 1768 | 1.2264          | 0.6583   | 0.6569 | 0.6614    |
| 0.3377        | 9.0   | 1989 | 1.2719          | 0.6447   | 0.6448 | 0.6480    |
| 0.1804        | 10.0  | 2210 | 1.2940          | 0.6481   | 0.6482 | 0.6531    |


### Framework versions

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