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metadata
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: []

swinv2-tiny-patch4-window16-256-finetuned-tekno24

This model is a fine-tuned version of 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