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End of training

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  1. .DS_Store +0 -0
  2. README.md +90 -0
  3. config.json +44 -0
  4. model.safetensors +3 -0
  5. preprocessor_config.json +22 -0
  6. training_args.bin +3 -0
.DS_Store ADDED
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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: google/vit-base-patch32-224-in21k
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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: results
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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: train
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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: 0.48125
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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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+ # results
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+
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+ This model is a fine-tuned version of [google/vit-base-patch32-224-in21k](https://huggingface.co/google/vit-base-patch32-224-in21k) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.5006
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+ - Accuracy: 0.4813
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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: 2e-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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+ - 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: 15
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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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+ | 2.0441 | 1.0 | 40 | 2.0365 | 0.25 |
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+ | 1.9219 | 2.0 | 80 | 1.9451 | 0.3063 |
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+ | 1.7429 | 3.0 | 120 | 1.8213 | 0.375 |
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+ | 1.5854 | 4.0 | 160 | 1.7126 | 0.4188 |
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+ | 1.4913 | 5.0 | 200 | 1.6547 | 0.4688 |
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+ | 1.3673 | 6.0 | 240 | 1.6200 | 0.4813 |
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+ | 1.2713 | 7.0 | 280 | 1.5822 | 0.475 |
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+ | 1.1907 | 8.0 | 320 | 1.5639 | 0.4875 |
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+ | 1.0516 | 9.0 | 360 | 1.5441 | 0.4875 |
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+ | 1.0037 | 10.0 | 400 | 1.5285 | 0.4813 |
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+ | 0.9538 | 11.0 | 440 | 1.5229 | 0.4813 |
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+ | 0.8983 | 12.0 | 480 | 1.5100 | 0.4813 |
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+ | 0.8616 | 13.0 | 520 | 1.5016 | 0.4938 |
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+ | 0.8417 | 14.0 | 560 | 1.5024 | 0.4813 |
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+ | 0.8078 | 15.0 | 600 | 1.5006 | 0.4813 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.44.2
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+ - Pytorch 2.4.1
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+ - Datasets 2.21.0
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+ - Tokenizers 0.19.1
config.json ADDED
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+ {
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+ "_name_or_path": "google/vit-base-patch32-224-in21k",
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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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+ "id2label": {
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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": 32,
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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": "4.44.2"
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+ }
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