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README.md ADDED
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+ ---
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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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+ model-index:
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+ - name: radiovers17v
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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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+ # radiovers17v
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+
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+ This model is a fine-tuned version of [](https://huggingface.co/) on the imagefolder dataset.
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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: 3.125e-05
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+ - train_batch_size: 8
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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: 80.0
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+
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+ ### Training results
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+
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.39.0.dev0
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
config.json ADDED
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+ {
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+ "architectures": [
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+ "ViTMAEForPreTraining"
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+ ],
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+ "attention_probs_dropout_prob": 0.0,
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+ "decoder_hidden_size": 512,
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+ "decoder_intermediate_size": 2048,
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+ "decoder_num_attention_heads": 16,
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+ "decoder_num_hidden_layers": 8,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.0,
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+ "hidden_size": 768,
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+ "image_size": 224,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 3072,
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+ "layer_norm_eps": 1e-12,
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+ "mask_ratio": 0.4,
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+ "model_type": "vit_mae",
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+ "norm_pix_loss": true,
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+ "num_attention_heads": 12,
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+ "num_channels": 3,
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+ "num_hidden_layers": 12,
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+ "patch_size": 16,
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+ "qkv_bias": true,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.39.0.dev0"
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+ }
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+ {
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+ "_valid_processor_keys": [
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+ "images",
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+ "do_resize",
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+ "size",
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+ "resample",
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+ "do_rescale",
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+ "image_processor_type": "ViTImageProcessor",
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+ "rescale_factor": 0.00392156862745098,
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+ "size": {
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+ "height": 224,
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+ "width": 224
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+ }
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+ }
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