---
license: apache-2.0
base_model: microsoft/swinv2-tiny-patch4-window16-256
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: swinv2-tiny-patch4-window16-256-finetuned-tekno24
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# swinv2-tiny-patch4-window16-256-finetuned-tekno24

This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window16-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window16-256) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2871
- Accuracy: 0.4224
- F1: 0.3135
- Precision: 0.4313
- Recall: 0.4224

## 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-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.3705        | 0.9963 | 68   | 1.3584          | 0.3563   | 0.2590 | 0.2886    | 0.3563 |
| 1.3515        | 1.9927 | 136  | 1.3392          | 0.3921   | 0.2606 | 0.3925    | 0.3921 |
| 1.3498        | 2.9890 | 204  | 1.3301          | 0.3912   | 0.2501 | 0.4247    | 0.3912 |
| 1.3351        | 4.0    | 273  | 1.3225          | 0.3930   | 0.2452 | 0.5371    | 0.3930 |
| 1.3212        | 4.9963 | 341  | 1.3128          | 0.3949   | 0.2556 | 0.4641    | 0.3949 |
| 1.3316        | 5.9927 | 409  | 1.3052          | 0.4004   | 0.2723 | 0.4129    | 0.4004 |
| 1.3269        | 6.9890 | 477  | 1.2980          | 0.4068   | 0.2850 | 0.4305    | 0.4068 |
| 1.3034        | 8.0    | 546  | 1.2927          | 0.4123   | 0.2924 | 0.4448    | 0.4123 |
| 1.3165        | 8.9963 | 614  | 1.2884          | 0.4215   | 0.3096 | 0.4453    | 0.4215 |
| 1.3306        | 9.9634 | 680  | 1.2871          | 0.4224   | 0.3135 | 0.4313    | 0.4224 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1