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  1. .gitignore +1 -0
  2. README.md +55 -0
  3. config.json +28 -0
  4. preprocessor_config.json +17 -0
  5. pytorch_model.bin +3 -0
  6. training_args.bin +3 -0
.gitignore ADDED
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+ checkpoint-*/
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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+ - image_folder
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+ model_index:
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+ - name: test_model_a
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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: image_folder
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+ type: image_folder
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+ args: default
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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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+ # test_model_a
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+
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+ This model is a fine-tuned version of [lysandre/tiny-vit-random](https://huggingface.co/lysandre/tiny-vit-random) on the image_folder 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: 5e-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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+ - training_steps: 40
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+
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+ ### Framework versions
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+
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+ - Transformers 4.8.2
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+ - Pytorch 1.9.0+cu102
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+ - Datasets 1.9.1.dev0
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+ - Tokenizers 0.10.3
config.json ADDED
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+ {
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+ "_name_or_path": "lysandre/tiny-vit-random",
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+ "architectures": [
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+ "ViTForImageClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.0,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.0,
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+ "hidden_size": 32,
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+ "id2label": {
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+ "0": "cat",
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+ "1": "dog"
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+ },
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+ "image_size": 224,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 32,
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+ "label2id": {
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+ "cat": "0",
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+ "dog": "1"
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+ },
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+ "layer_norm_eps": 1e-12,
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+ "model_type": "vit",
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+ "num_attention_heads": 2,
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+ "num_channels": 3,
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+ "num_hidden_layers": 2,
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+ "patch_size": 16,
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+ "transformers_version": "4.8.2"
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+ }
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+ {
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+ "do_normalize": true,
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+ "do_resize": true,
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+ "feature_extractor_type": "ViTFeatureExtractor",
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+ "image_mean": [
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+ 0.5,
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+ 0.5,
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+ 0.5
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+ ],
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+ "image_std": [
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+ 0.5,
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+ 0.5,
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+ 0.5
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+ ],
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+ "resample": 2,
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+ "size": 224
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+ }
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