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swinv2-tiny-patch4-window8-256-RD-FIX

Image Classification
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swinv2
Generated from Trainer
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  1. README.md +117 -0
  2. model.safetensors +1 -1
  3. runs/Dec26_06-28-55_95da625fa085/events.out.tfevents.1735194602.95da625fa085.1076.0 +2 -2
README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: microsoft/swinv2-tiny-patch4-window8-256
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - imagefolder
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: swinv2-tiny-patch4-window8-256-RD-FIX
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+ results:
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+ - task:
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+ name: Image Classification
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+ type: image-classification
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+ dataset:
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+ name: imagefolder
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+ type: imagefolder
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+ config: default
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+ split: validation
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+ args: default
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.782608695652174
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # swinv2-tiny-patch4-window8-256-RD-FIX
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+
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+ This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5014
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+ - Accuracy: 0.7826
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 64
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+ - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - num_epochs: 40
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-------:|:----:|:---------------:|:--------:|
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+ | No log | 0.8571 | 3 | 1.1955 | 0.4565 |
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+ | No log | 1.8571 | 6 | 1.1280 | 0.5 |
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+ | No log | 2.8571 | 9 | 1.0565 | 0.4783 |
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+ | 4.8751 | 3.8571 | 12 | 0.9184 | 0.5870 |
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+ | 4.8751 | 4.8571 | 15 | 0.8208 | 0.5870 |
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+ | 4.8751 | 5.8571 | 18 | 0.7310 | 0.6087 |
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+ | 3.6315 | 6.8571 | 21 | 0.6951 | 0.7174 |
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+ | 3.6315 | 7.8571 | 24 | 0.6772 | 0.7174 |
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+ | 3.6315 | 8.8571 | 27 | 0.6626 | 0.7174 |
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+ | 2.8559 | 9.8571 | 30 | 0.5987 | 0.7826 |
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+ | 2.8559 | 10.8571 | 33 | 0.5431 | 0.8261 |
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+ | 2.8559 | 11.8571 | 36 | 0.6193 | 0.6739 |
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+ | 2.8559 | 12.8571 | 39 | 0.6475 | 0.7174 |
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+ | 2.3617 | 13.8571 | 42 | 0.5725 | 0.7174 |
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+ | 2.3617 | 14.8571 | 45 | 0.5794 | 0.7826 |
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+ | 2.3617 | 15.8571 | 48 | 0.5292 | 0.7826 |
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+ | 2.1506 | 16.8571 | 51 | 0.5988 | 0.7391 |
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+ | 2.1506 | 17.8571 | 54 | 0.6548 | 0.7174 |
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+ | 2.1506 | 18.8571 | 57 | 0.5131 | 0.8261 |
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+ | 1.9498 | 19.8571 | 60 | 0.4700 | 0.8478 |
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+ | 1.9498 | 20.8571 | 63 | 0.5254 | 0.8043 |
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+ | 1.9498 | 21.8571 | 66 | 0.5451 | 0.7826 |
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+ | 1.9498 | 22.8571 | 69 | 0.5304 | 0.7609 |
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+ | 1.422 | 23.8571 | 72 | 0.5105 | 0.8043 |
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+ | 1.422 | 24.8571 | 75 | 0.4685 | 0.7826 |
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+ | 1.422 | 25.8571 | 78 | 0.4875 | 0.8261 |
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+ | 1.3044 | 26.8571 | 81 | 0.5492 | 0.7826 |
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+ | 1.3044 | 27.8571 | 84 | 0.5202 | 0.7826 |
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+ | 1.3044 | 28.8571 | 87 | 0.4737 | 0.8261 |
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+ | 1.2464 | 29.8571 | 90 | 0.4398 | 0.8478 |
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+ | 1.2464 | 30.8571 | 93 | 0.4753 | 0.8043 |
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+ | 1.2464 | 31.8571 | 96 | 0.4913 | 0.8043 |
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+ | 1.2464 | 32.8571 | 99 | 0.5262 | 0.7826 |
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+ | 1.1614 | 33.8571 | 102 | 0.5280 | 0.7826 |
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+ | 1.1614 | 34.8571 | 105 | 0.5252 | 0.7609 |
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+ | 1.1614 | 35.8571 | 108 | 0.5127 | 0.7826 |
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+ | 1.045 | 36.8571 | 111 | 0.5061 | 0.7826 |
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+ | 1.045 | 37.8571 | 114 | 0.5012 | 0.7826 |
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+ | 1.045 | 38.8571 | 117 | 0.5025 | 0.7826 |
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+ | 0.9391 | 39.8571 | 120 | 0.5014 | 0.7826 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.47.1
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+ - Pytorch 2.5.1+cu121
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+ - Datasets 3.2.0
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+ - Tokenizers 0.21.0
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