End of training

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
+model-index:
+- name: urinary_carcinoma_classifier_g002
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: train[:63]
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9230769230769231
+---
+
+<!-- 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_g002
+
+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: 0.3544
+- Accuracy: 0.9231
+
+## 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    | 0.6814          | 0.5385   |
+| No log        | 2.0   | 2    | 0.6743          | 0.6923   |
+| No log        | 3.0   | 3    | 0.6449          | 0.7692   |
+| No log        | 4.0   | 4    | 0.6149          | 0.7692   |
+| No log        | 5.0   | 5    | 0.5980          | 0.7692   |
+| No log        | 6.0   | 6    | 0.5855          | 0.7692   |
+| No log        | 7.0   | 7    | 0.5663          | 0.7692   |
+| No log        | 8.0   | 8    | 0.5675          | 0.7692   |
+| No log        | 9.0   | 9    | 0.5530          | 0.7692   |
+| 0.637         | 10.0  | 10   | 0.5246          | 0.8462   |
+| 0.637         | 11.0  | 11   | 0.5135          | 0.7692   |
+| 0.637         | 12.0  | 12   | 0.5296          | 0.8462   |
+| 0.637         | 13.0  | 13   | 0.5340          | 0.8462   |
+| 0.637         | 14.0  | 14   | 0.4781          | 0.9231   |
+| 0.637         | 15.0  | 15   | 0.4870          | 0.8462   |
+| 0.637         | 16.0  | 16   | 0.4701          | 0.8462   |
+| 0.637         | 17.0  | 17   | 0.4521          | 1.0      |
+| 0.637         | 18.0  | 18   | 0.4266          | 0.9231   |
+| 0.637         | 19.0  | 19   | 0.4220          | 0.9231   |
+| 0.4474        | 20.0  | 20   | 0.3837          | 0.9231   |
+| 0.4474        | 21.0  | 21   | 0.4257          | 0.8462   |
+| 0.4474        | 22.0  | 22   | 0.4093          | 0.9231   |
+| 0.4474        | 23.0  | 23   | 0.4019          | 1.0      |
+| 0.4474        | 24.0  | 24   | 0.4578          | 0.8462   |
+| 0.4474        | 25.0  | 25   | 0.3932          | 1.0      |
+| 0.4474        | 26.0  | 26   | 0.3838          | 1.0      |
+| 0.4474        | 27.0  | 27   | 0.3627          | 1.0      |
+| 0.4474        | 28.0  | 28   | 0.3862          | 0.9231   |
+| 0.4474        | 29.0  | 29   | 0.3624          | 0.9231   |
+| 0.3102        | 30.0  | 30   | 0.3544          | 0.9231   |
+
+
+### Framework versions
+
+- Transformers 4.42.4
+- Pytorch 2.3.1
+- Datasets 2.20.0
+- Tokenizers 0.19.1

model.safetensors

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