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---
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
should probably proofread and complete it, then remove this comment. -->
# 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
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