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finetuned_model

Image Classification
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vit
Generated from Trainer
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  1. README.md +54 -0
  2. all_results.json +13 -0
  3. config.json +40 -0
  4. eval_results.json +9 -0
  5. model.safetensors +3 -0
  6. preprocessor_config.json +22 -0
  7. pytorch_model.bin +3 -0
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  34. train_results.json +7 -0
  35. trainer_state.json +28 -0
  36. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: google/vit-base-patch16-224
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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: finetuned_model
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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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+ # finetuned_model
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+
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+ This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) 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: 5e-05
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+ - train_batch_size: 64
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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: 50
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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 4.38.2
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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+ {
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+ "epoch": 50.0,
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+ "eval_accuracy": 0.7142857142857143,
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+ "eval_f1": 0.4205128205128205,
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+ "eval_loss": 0.4927063584327698,
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+ "eval_runtime": 11.2641,
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+ "eval_samples_per_second": 2.486,
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+ "eval_steps_per_second": 0.355,
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+ "train_loss": 0.5841025924682617,
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+ "train_runtime": 1156.5484,
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+ "train_samples_per_second": 1.21,
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+ "train_steps_per_second": 0.086
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+ }
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+ {
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+ "_name_or_path": "google/vit-base-patch16-224",
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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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+ "encoder_stride": 16,
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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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+ "id2label": {
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+ "0": "aeroplane",
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+ "1": "blackboard",
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+ "2": "books",
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+ "3": "bridge",
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+ "4": "truck",
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+ "5": "water"
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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": 3072,
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+ "label2id": {
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+ "aeroplane": "0",
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+ "books": "2",
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+ "bridge": "3",
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+ "truck": "4",
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+ "water": "5"
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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": 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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+ "problem_type": "single_label_classification",
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+ "qkv_bias": true,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.38.2"
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+ }
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+ "image_mean": [
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+ 0.5,
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+ "image_processor_type": "ViTFeatureExtractor",
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