Model save

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: google/vit-base-patch16-224-in21k
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: finetuned-arsenic
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9986902423051736
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# finetuned-arsenic
+
+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 imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0039
+- Accuracy: 0.9987
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0002
+- train_batch_size: 16
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 4
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
+|:-------------:|:------:|:----:|:---------------:|:--------:|
+| 0.3535        | 0.1848 | 100  | 0.2896          | 0.8762   |
+| 0.1869        | 0.3697 | 200  | 0.1380          | 0.9574   |
+| 0.1594        | 0.5545 | 300  | 0.1052          | 0.9679   |
+| 0.117         | 0.7394 | 400  | 0.0502          | 0.9836   |
+| 0.0796        | 0.9242 | 500  | 0.0881          | 0.9673   |
+| 0.0795        | 1.1091 | 600  | 0.0698          | 0.9751   |
+| 0.0644        | 1.2939 | 700  | 0.0342          | 0.9895   |
+| 0.054         | 1.4787 | 800  | 0.0344          | 0.9882   |
+| 0.0776        | 1.6636 | 900  | 0.0292          | 0.9915   |
+| 0.0143        | 1.8484 | 1000 | 0.0242          | 0.9928   |
+| 0.0597        | 2.0333 | 1100 | 0.0132          | 0.9954   |
+| 0.0285        | 2.2181 | 1200 | 0.0263          | 0.9928   |
+| 0.0349        | 2.4030 | 1300 | 0.0070          | 0.9980   |
+| 0.0164        | 2.5878 | 1400 | 0.0067          | 0.9987   |
+| 0.0058        | 2.7726 | 1500 | 0.0119          | 0.9954   |
+| 0.0013        | 2.9575 | 1600 | 0.0066          | 0.9987   |
+| 0.0028        | 3.1423 | 1700 | 0.0052          | 0.9987   |
+| 0.0028        | 3.3272 | 1800 | 0.0052          | 0.9987   |
+| 0.0244        | 3.5120 | 1900 | 0.0264          | 0.9928   |
+| 0.002         | 3.6969 | 2000 | 0.0025          | 0.9993   |
+| 0.0054        | 3.8817 | 2100 | 0.0039          | 0.9987   |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.1+cu121
+- Datasets 3.0.1
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "google/vit-base-patch16-224-in21k",
+  "architectures": [
+    "ViTForImageClassification"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "encoder_stride": 16,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "infacted",
+    "1": "not_infacted"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "infacted": "0",
+    "not_infacted": "1"
+  },
+  "layer_norm_eps": 1e-12,
+  "model_type": "vit",
+  "num_attention_heads": 12,
+  "num_channels": 3,
+  "num_hidden_layers": 12,
+  "patch_size": 16,
+  "problem_type": "single_label_classification",
+  "qkv_bias": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.44.2"
+}

model.safetensors

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preprocessor_config.json

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+{
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "image_processor_type": "ViTFeatureExtractor",
+  "image_std": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "resample": 2,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "height": 224,
+    "width": 224
+  }
+}

runs/Oct03_19-19-48_a15518d9a370/events.out.tfevents.1727983241.a15518d9a370.688.0

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runs/Oct03_19-44-26_a15518d9a370/events.out.tfevents.1727984686.a15518d9a370.688.4

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training_args.bin

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