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End of training

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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-in21k
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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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+ metrics:
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+ - accuracy
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+ - f1
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+ model-index:
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+ - name: Corn-Plant-1-Epochs-Model
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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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+ config: data
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+ split: train
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+ args: data
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.8433734939759037
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+ - name: F1
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+ type: f1
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+ value: 0.8932628786809459
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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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+ # Corn-Plant-1-Epochs-Model
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+
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+ This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the image_folder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4730
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+ - Accuracy: 0.8434
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+ - F1: 0.8933
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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: 1
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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 | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | 0.646 | 1.0 | 94 | 0.4730 | 0.8434 | 0.8933 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.0
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+ - Pytorch 2.0.0
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+ - Datasets 2.1.0
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+ - Tokenizers 0.14.1
all_results.json ADDED
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+ {
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+ "epoch": 1.0,
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+ "eval_accuracy": 0.8433734939759037,
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+ "eval_f1": 0.8932628786809459,
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+ "eval_loss": 0.473047137260437,
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+ "eval_runtime": 2.4782,
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+ "eval_samples": 1493,
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+ "eval_samples_per_second": 66.985,
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+ "eval_steps_per_second": 4.439,
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+ "total_flos": 1.1569761437965517e+17,
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+ "train_loss": 0.6459824582363697,
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+ "train_runtime": 145.4821,
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+ "train_samples": 1493,
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+ "train_samples_per_second": 10.262,
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+ "train_steps_per_second": 0.646
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+ }
config.json ADDED
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+ {
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+ "_name_or_path": "google/vit-base-patch16-224-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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+ "hidden_size": 768,
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+ "id2label": {
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+ "0": 0,
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+ "1": 1,
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+ "2": 2,
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+ "3": 3
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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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+ "0": 0,
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+ "1": 1,
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+ "2": 2,
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+ "3": 3
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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": "4.35.0"
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+ }
eval_results.json ADDED
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+ {
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+ "epoch": 1.0,
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+ "eval_accuracy": 0.8433734939759037,
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+ "eval_f1": 0.8932628786809459,
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+ "eval_loss": 0.473047137260437,
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+ "eval_runtime": 2.4782,
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+ "eval_samples": 1493,
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+ "eval_samples_per_second": 66.985,
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+ "eval_steps_per_second": 4.439
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+ }
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preprocessor_config.json ADDED
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+ {
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+ "do_rescale": true,
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+ "image_mean": [
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+ "image_processor_type": "ViTImageProcessor",
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+ "resample": 2,
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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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train_results.json ADDED
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+ {
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+ "train_steps_per_second": 0.646
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