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: image_classification
+  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: 0.59375
+---
+
+<!-- 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. -->
+
+# image_classification
+
+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: 1.2364
+- Accuracy: 0.5938
+
+## 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: 15
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 2.0702        | 1.0   | 10   | 2.0666          | 0.1437   |
+| 2.0583        | 2.0   | 20   | 2.0476          | 0.2125   |
+| 2.0291        | 3.0   | 30   | 2.0018          | 0.3      |
+| 1.9639        | 4.0   | 40   | 1.9175          | 0.3563   |
+| 1.8582        | 5.0   | 50   | 1.7997          | 0.4375   |
+| 1.7385        | 6.0   | 60   | 1.6756          | 0.4625   |
+| 1.5984        | 7.0   | 70   | 1.5469          | 0.4625   |
+| 1.4739        | 8.0   | 80   | 1.4684          | 0.5188   |
+| 1.3737        | 9.0   | 90   | 1.4090          | 0.5125   |
+| 1.2719        | 10.0  | 100  | 1.3740          | 0.525    |
+| 1.2072        | 11.0  | 110  | 1.3527          | 0.55     |
+| 1.1158        | 12.0  | 120  | 1.3118          | 0.5188   |
+| 1.0487        | 13.0  | 130  | 1.2349          | 0.6      |
+| 0.9873        | 14.0  | 140  | 1.2931          | 0.525    |
+| 0.8928        | 15.0  | 150  | 1.2731          | 0.55     |
+
+
+### Framework versions
+
+- Transformers 4.42.4
+- Pytorch 2.4.0+cu121
+- Datasets 2.21.0
+- Tokenizers 0.19.1

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