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End of training

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  1. README.md +72 -0
  2. config.json +111 -0
  3. model.safetensors +3 -0
  4. preprocessor_config.json +22 -0
  5. 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: microsoft/cvt-w24-384-22k
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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: cvt-w24-384-22k-finetuned-LeafBack-v1
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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: validation
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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: 1.0
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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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+ # cvt-w24-384-22k-finetuned-LeafBack-v1
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+
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+ This model is a fine-tuned version of [microsoft/cvt-w24-384-22k](https://huggingface.co/microsoft/cvt-w24-384-22k) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0009
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+ - Accuracy: 1.0
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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: 0.0005
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+ - train_batch_size: 32
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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 4.38.1
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+ - Pytorch 1.10.0+cu111
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+ - Datasets 2.17.1
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+ - Tokenizers 0.15.2
config.json ADDED
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+ {
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+ "_name_or_path": "microsoft/cvt-w24-384-22k",
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+ "architectures": [
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+ "CvtForImageClassification"
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+ ],
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+ "embed_dim": [
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+ ],
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+ "id2label": {
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+ "0": "leafmold",
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+ "1": "powdery"
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+ },
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+ "initializer_range": 0.02,
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+ "kernel_qkv": [
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+ "layer_norm_eps": 1e-12,
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+ "model_type": "cvt",
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+ "num_channels": 3,
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+ "problem_type": "single_label_classification",
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+ "qkv_bias": [
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+ "qkv_projection_method": [
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.38.1"
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+ }
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