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swinv2-tiny-patch4-window8-256-RD-da-colab

Image Classification
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swinv2
Generated from Trainer
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  2. model.safetensors +1 -1
  3. runs/Dec09_18-08-28_6d653b36a071/events.out.tfevents.1733767714.6d653b36a071.2332.2 +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-da-colab
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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: 0.49454545454545457
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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-da-colab
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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: 11.3523
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+ - Accuracy: 0.4945
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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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+ | 0.1347 | 1.0 | 96 | 10.0386 | 0.4982 |
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+ | 0.1556 | 2.0 | 192 | 9.5018 | 0.5 |
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+ | 0.1051 | 3.0 | 288 | 9.9516 | 0.4982 |
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+ | 0.1154 | 4.0 | 384 | 10.8351 | 0.4945 |
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+ | 0.0909 | 5.0 | 480 | 11.6091 | 0.4945 |
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+ | 0.0923 | 6.0 | 576 | 9.0530 | 0.5 |
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+ | 0.1089 | 7.0 | 672 | 11.6765 | 0.4927 |
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+ | 0.0959 | 8.0 | 768 | 11.5132 | 0.4982 |
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+ | 0.1266 | 9.0 | 864 | 10.2420 | 0.5036 |
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+ | 0.106 | 10.0 | 960 | 11.1262 | 0.4945 |
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+ | 0.0831 | 11.0 | 1056 | 11.5815 | 0.4964 |
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+ | 0.0819 | 12.0 | 1152 | 11.6394 | 0.4964 |
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+ | 0.0862 | 13.0 | 1248 | 10.9660 | 0.4982 |
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+ | 0.0754 | 14.0 | 1344 | 9.5463 | 0.4982 |
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+ | 0.06 | 15.0 | 1440 | 10.2678 | 0.4964 |
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+ | 0.0828 | 16.0 | 1536 | 11.4973 | 0.4927 |
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+ | 0.0675 | 17.0 | 1632 | 10.5019 | 0.4964 |
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+ | 0.0687 | 18.0 | 1728 | 10.6483 | 0.4982 |
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+ | 0.0548 | 19.0 | 1824 | 11.2166 | 0.4964 |
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+ | 0.0658 | 20.0 | 1920 | 11.5459 | 0.4945 |
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+ | 0.0565 | 21.0 | 2016 | 11.5899 | 0.4945 |
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+ | 0.0807 | 22.0 | 2112 | 10.7066 | 0.5 |
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+ | 0.0289 | 23.0 | 2208 | 10.6253 | 0.4982 |
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+ | 0.0755 | 24.0 | 2304 | 10.4856 | 0.5018 |
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+ | 0.0483 | 25.0 | 2400 | 11.3838 | 0.4964 |
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+ | 0.0732 | 26.0 | 2496 | 11.1971 | 0.4927 |
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+ | 0.1424 | 27.0 | 2592 | 11.4581 | 0.4945 |
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+ | 0.0814 | 28.0 | 2688 | 11.3341 | 0.4945 |
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+ | 0.101 | 29.0 | 2784 | 11.5705 | 0.4927 |
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+ | 0.0894 | 30.0 | 2880 | 11.5259 | 0.4927 |
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+ | 0.0707 | 31.0 | 2976 | 11.1753 | 0.4945 |
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+ | 0.1289 | 32.0 | 3072 | 10.5668 | 0.4964 |
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+ | 0.0991 | 33.0 | 3168 | 11.1013 | 0.4945 |
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+ | 0.0615 | 34.0 | 3264 | 11.0973 | 0.4945 |
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+ | 0.0784 | 35.0 | 3360 | 11.0716 | 0.4945 |
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+ | 0.0792 | 36.0 | 3456 | 11.0241 | 0.4945 |
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+ | 0.1032 | 37.0 | 3552 | 11.2338 | 0.4945 |
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+ | 0.0837 | 38.0 | 3648 | 11.4256 | 0.4927 |
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+ | 0.0722 | 39.0 | 3744 | 11.3971 | 0.4945 |
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+ | 0.079 | 40.0 | 3840 | 11.3523 | 0.4945 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.46.3
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+ - Pytorch 2.5.1+cu121
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+ - Datasets 3.1.0
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+ - Tokenizers 0.20.3
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