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RobertoSonic
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swinv2-tiny-patch4-window8-256-dmae-humeda-DAV65

Image Classification
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Safetensors
swinv2
Generated from Trainer
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  1. README.md +109 -0
  2. model.safetensors +1 -1
  3. runs/Mar20_07-20-59_2ac3722f116a/events.out.tfevents.1742455282.2ac3722f116a.12697.0 +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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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: swinv2-tiny-patch4-window8-256-dmae-humeda-DAV65
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+ results: []
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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-dmae-humeda-DAV65
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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 an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4692
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+ - Accuracy: 0.8686
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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: 6e-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 OptimizerNames.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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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 45
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+ - mixed_precision_training: Native AMP
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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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+ | 1.1096 | 1.0 | 15 | 1.0206 | 0.48 |
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+ | 0.7949 | 2.0 | 30 | 0.5637 | 0.8057 |
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+ | 0.6305 | 3.0 | 45 | 0.3961 | 0.8457 |
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+ | 0.4475 | 4.0 | 60 | 0.3464 | 0.8629 |
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+ | 0.4342 | 5.0 | 75 | 0.3489 | 0.8629 |
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+ | 0.3843 | 6.0 | 90 | 0.3304 | 0.8457 |
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+ | 0.3059 | 7.0 | 105 | 0.3037 | 0.88 |
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+ | 0.2993 | 8.0 | 120 | 0.3286 | 0.8686 |
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+ | 0.2799 | 9.0 | 135 | 0.4499 | 0.8457 |
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+ | 0.302 | 10.0 | 150 | 0.2965 | 0.8857 |
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+ | 0.2445 | 11.0 | 165 | 0.2569 | 0.8857 |
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+ | 0.2317 | 12.0 | 180 | 0.4269 | 0.8286 |
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+ | 0.2189 | 13.0 | 195 | 0.4250 | 0.8514 |
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+ | 0.2001 | 14.0 | 210 | 0.3725 | 0.8743 |
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+ | 0.1924 | 15.0 | 225 | 0.3042 | 0.8571 |
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+ | 0.1617 | 16.0 | 240 | 0.4525 | 0.8686 |
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+ | 0.131 | 17.0 | 255 | 0.4021 | 0.8457 |
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+ | 0.1491 | 18.0 | 270 | 0.3316 | 0.8571 |
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+ | 0.1576 | 19.0 | 285 | 0.3288 | 0.8857 |
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+ | 0.1189 | 20.0 | 300 | 0.3464 | 0.88 |
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+ | 0.1384 | 21.0 | 315 | 0.3618 | 0.8857 |
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+ | 0.1109 | 22.0 | 330 | 0.3548 | 0.8914 |
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+ | 0.0985 | 23.0 | 345 | 0.3908 | 0.8857 |
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+ | 0.1095 | 24.0 | 360 | 0.4517 | 0.8743 |
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+ | 0.1007 | 25.0 | 375 | 0.5406 | 0.8743 |
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+ | 0.192 | 26.0 | 390 | 0.5257 | 0.8686 |
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+ | 0.093 | 27.0 | 405 | 0.4442 | 0.8686 |
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+ | 0.1337 | 28.0 | 420 | 0.5376 | 0.8629 |
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+ | 0.0737 | 29.0 | 435 | 0.4627 | 0.8686 |
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+ | 0.0932 | 30.0 | 450 | 0.4371 | 0.8914 |
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+ | 0.0638 | 31.0 | 465 | 0.4741 | 0.8971 |
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+ | 0.0796 | 32.0 | 480 | 0.4220 | 0.88 |
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+ | 0.0674 | 33.0 | 495 | 0.4432 | 0.9029 |
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+ | 0.0466 | 34.0 | 510 | 0.4385 | 0.8914 |
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+ | 0.0586 | 35.0 | 525 | 0.4614 | 0.8971 |
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+ | 0.0634 | 36.0 | 540 | 0.4855 | 0.8857 |
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+ | 0.0867 | 37.0 | 555 | 0.4716 | 0.88 |
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+ | 0.0721 | 38.0 | 570 | 0.4353 | 0.8914 |
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+ | 0.0572 | 39.0 | 585 | 0.4443 | 0.8914 |
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+ | 0.0613 | 40.0 | 600 | 0.4655 | 0.8857 |
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+ | 0.0911 | 41.0 | 615 | 0.4462 | 0.8971 |
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+ | 0.0691 | 42.0 | 630 | 0.4922 | 0.88 |
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+ | 0.0767 | 43.0 | 645 | 0.4702 | 0.8743 |
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+ | 0.0763 | 44.0 | 660 | 0.4670 | 0.8743 |
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+ | 0.055 | 45.0 | 675 | 0.4692 | 0.8686 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.48.3
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+ - Pytorch 2.6.0+cu124
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+ - Datasets 3.4.1
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+ - Tokenizers 0.21.1
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