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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: microsoft/swinv2-tiny-patch4-window16-256
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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: Action_agent
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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: train
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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: 0.7914285714285715
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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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+ # Action_agent
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+
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+ This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window16-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window16-256) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6412
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+ - Accuracy: 0.7914
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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: 1e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 10
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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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+ | 2.039 | 0.32 | 100 | 1.7706 | 0.4848 |
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+ | 1.3695 | 0.64 | 200 | 1.0886 | 0.6457 |
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+ | 1.099 | 0.96 | 300 | 0.9092 | 0.68 |
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+ | 1.0011 | 1.27 | 400 | 0.8183 | 0.7171 |
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+ | 0.8437 | 1.59 | 500 | 0.7674 | 0.7190 |
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+ | 0.8613 | 1.91 | 600 | 0.7168 | 0.7410 |
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+ | 0.7427 | 2.23 | 700 | 0.7270 | 0.7352 |
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+ | 0.693 | 2.55 | 800 | 0.6801 | 0.7676 |
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+ | 0.7789 | 2.87 | 900 | 0.6832 | 0.7590 |
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+ | 0.6863 | 3.18 | 1000 | 0.6655 | 0.7752 |
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+ | 0.6437 | 3.5 | 1100 | 0.6382 | 0.7771 |
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+ | 0.6741 | 3.82 | 1200 | 0.6446 | 0.7790 |
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+ | 0.5871 | 4.14 | 1300 | 0.6551 | 0.7838 |
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+ | 0.6051 | 4.46 | 1400 | 0.6970 | 0.7638 |
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+ | 0.5175 | 4.78 | 1500 | 0.6553 | 0.7790 |
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+ | 0.5795 | 5.1 | 1600 | 0.6667 | 0.7771 |
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+ | 0.4919 | 5.41 | 1700 | 0.6317 | 0.7905 |
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+ | 0.4986 | 5.73 | 1800 | 0.6486 | 0.7810 |
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+ | 0.5104 | 6.05 | 1900 | 0.6700 | 0.7743 |
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+ | 0.4919 | 6.37 | 2000 | 0.6528 | 0.7819 |
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+ | 0.5144 | 6.69 | 2100 | 0.6355 | 0.7876 |
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+ | 0.5554 | 7.01 | 2200 | 0.6552 | 0.7771 |
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+ | 0.5389 | 7.32 | 2300 | 0.6361 | 0.7876 |
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+ | 0.5751 | 7.64 | 2400 | 0.6377 | 0.7905 |
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+ | 0.4743 | 7.96 | 2500 | 0.6417 | 0.7867 |
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+ | 0.4519 | 8.28 | 2600 | 0.6309 | 0.7895 |
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+ | 0.5058 | 8.6 | 2700 | 0.6453 | 0.7867 |
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+ | 0.4754 | 8.92 | 2800 | 0.6414 | 0.7905 |
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+ | 0.4637 | 9.24 | 2900 | 0.6330 | 0.7905 |
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+ | 0.5028 | 9.55 | 3000 | 0.6418 | 0.7857 |
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+ | 0.4227 | 9.87 | 3100 | 0.6412 | 0.7914 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.39.3
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+ - Pytorch 2.1.2
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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