End of training

README.md

@@ -0,0 +1,107 @@
+---
+license: apache-2.0
+base_model: google/vit-base-patch16-224-in21k
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: urinary_carcinoma_classifier_g001
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: train[:23]
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.6
+---
+
+<!-- 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. -->
+
+# urinary_carcinoma_classifier_g001
+
+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: 0.6827
+- Accuracy: 0.6
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 64
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 30
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 1    | 0.7147          | 0.4      |
+| No log        | 2.0   | 2    | 0.7114          | 0.4      |
+| No log        | 3.0   | 3    | 0.6968          | 0.2      |
+| No log        | 4.0   | 4    | 0.7055          | 0.4      |
+| No log        | 5.0   | 5    | 0.6741          | 0.4      |
+| No log        | 6.0   | 6    | 0.6580          | 0.6      |
+| No log        | 7.0   | 7    | 0.6092          | 0.6      |
+| No log        | 8.0   | 8    | 0.6200          | 0.6      |
+| No log        | 9.0   | 9    | 0.6139          | 0.6      |
+| 0.3094        | 10.0  | 10   | 0.5969          | 0.6      |
+| 0.3094        | 11.0  | 11   | 0.5677          | 0.6      |
+| 0.3094        | 12.0  | 12   | 0.6021          | 0.6      |
+| 0.3094        | 13.0  | 13   | 0.6189          | 0.6      |
+| 0.3094        | 14.0  | 14   | 0.6054          | 0.6      |
+| 0.3094        | 15.0  | 15   | 0.6240          | 0.6      |
+| 0.3094        | 16.0  | 16   | 0.5388          | 0.6      |
+| 0.3094        | 17.0  | 17   | 0.5320          | 0.6      |
+| 0.3094        | 18.0  | 18   | 0.5973          | 0.6      |
+| 0.3094        | 19.0  | 19   | 0.5981          | 0.8      |
+| 0.1723        | 20.0  | 20   | 0.6531          | 0.6      |
+| 0.1723        | 21.0  | 21   | 0.6246          | 0.6      |
+| 0.1723        | 22.0  | 22   | 0.6718          | 0.6      |
+| 0.1723        | 23.0  | 23   | 0.6692          | 0.6      |
+| 0.1723        | 24.0  | 24   | 0.6537          | 0.6      |
+| 0.1723        | 25.0  | 25   | 0.4650          | 0.6      |
+| 0.1723        | 26.0  | 26   | 0.6873          | 0.6      |
+| 0.1723        | 27.0  | 27   | 0.6461          | 0.6      |
+| 0.1723        | 28.0  | 28   | 0.5876          | 0.8      |
+| 0.1723        | 29.0  | 29   | 0.4898          | 0.6      |
+| 0.1049        | 30.0  | 30   | 0.6827          | 0.6      |
+
+
+### Framework versions
+
+- Transformers 4.42.4
+- Pytorch 2.3.1
+- Datasets 2.20.0
+- Tokenizers 0.19.1

model.safetensors

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