Model save

README.md

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+---
+license: apache-2.0
+base_model: google/vit-base-patch16-224-in21k
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: vit-base-patch16-224-in21k-laneclassifierasphaltconcrete-detectorVITmain50epochs
+  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:
+        accuracy: 1.0
+    - name: F1
+      type: f1
+      value:
+        f1: 1.0
+    - name: Precision
+      type: precision
+      value:
+        precision: 1.0
+    - name: Recall
+      type: recall
+      value:
+        recall: 1.0
+---
+
+<!-- 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. -->
+
+# vit-base-patch16-224-in21k-laneclassifierasphaltconcrete-detectorVITmain50epochs
+
+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: 0.0004
+- Accuracy: {'accuracy': 1.0}
+- F1: {'f1': 1.0}
+- Precision: {'precision': 1.0}
+- Recall: {'recall': 1.0}
+
+## 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: 5e-05
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 8
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy                         | F1                         | Precision                         | Recall                         |
+|:-------------:|:------:|:----:|:---------------:|:--------------------------------:|:--------------------------:|:---------------------------------:|:------------------------------:|
+| 0.0576        | 0.9933 | 111  | 0.0139          | {'accuracy': 0.9977628635346756} | {'f1': 0.9966709613995368} | {'precision': 0.9985795454545454} | {'recall': 0.9947916666666667} |
+| 0.0365        | 1.9955 | 223  | 0.0012          | {'accuracy': 1.0}                | {'f1': 1.0}                | {'precision': 1.0}                | {'recall': 1.0}                |
+| 0.0009        | 2.9978 | 335  | 0.0008          | {'accuracy': 1.0}                | {'f1': 1.0}                | {'precision': 1.0}                | {'recall': 1.0}                |
+| 0.0007        | 4.0    | 447  | 0.0007          | {'accuracy': 1.0}                | {'f1': 1.0}                | {'precision': 1.0}                | {'recall': 1.0}                |
+| 0.0006        | 4.9933 | 558  | 0.0005          | {'accuracy': 1.0}                | {'f1': 1.0}                | {'precision': 1.0}                | {'recall': 1.0}                |
+| 0.0005        | 5.9955 | 670  | 0.0005          | {'accuracy': 1.0}                | {'f1': 1.0}                | {'precision': 1.0}                | {'recall': 1.0}                |
+| 0.0005        | 6.9978 | 782  | 0.0004          | {'accuracy': 1.0}                | {'f1': 1.0}                | {'precision': 1.0}                | {'recall': 1.0}                |
+| 0.0005        | 7.9463 | 888  | 0.0004          | {'accuracy': 1.0}                | {'f1': 1.0}                | {'precision': 1.0}                | {'recall': 1.0}                |
+
+
+### Framework versions
+
+- Transformers 4.43.3
+- Pytorch 2.3.1
+- Datasets 2.20.0
+- Tokenizers 0.19.1

runs/Sep10_13-40-16_CARL-Mechanical-PC/events.out.tfevents.1725946826.CARL-Mechanical-PC.14572.1

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