Model save

README.md

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+---
+license: apache-2.0
+base_model: google/vit-base-patch16-224
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: cards-vit-base-patch16-224-finetuned-v1
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: test
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.3192410001773364
+---
+
+<!-- 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. -->
+
+# cards-vit-base-patch16-224-finetuned-v1
+
+This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.6835
+- Accuracy: 0.3192
+
+## 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: 64
+- eval_batch_size: 64
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 256
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
+|:-------------:|:------:|:----:|:---------------:|:--------:|
+| 1.7866        | 0.9993 | 378  | 1.7677          | 0.2746   |
+| 1.7457        | 1.9987 | 756  | 1.7163          | 0.2990   |
+| 1.7123        | 2.9980 | 1134 | 1.6862          | 0.3007   |
+| 1.6607        | 4.0    | 1513 | 1.6823          | 0.3081   |
+| 1.6188        | 4.9993 | 1891 | 1.6907          | 0.3108   |
+| 1.6009        | 5.9987 | 2269 | 1.6773          | 0.3150   |
+| 1.5485        | 6.9980 | 2647 | 1.6720          | 0.3198   |
+| 1.5133        | 8.0    | 3026 | 1.6811          | 0.3199   |
+| 1.5001        | 8.9993 | 3404 | 1.6821          | 0.3209   |
+| 1.4303        | 9.9934 | 3780 | 1.6835          | 0.3192   |
+
+
+### Framework versions
+
+- Transformers 4.40.1
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1

runs/May14_14-49-56_e2e-66-39/events.out.tfevents.1715678401.e2e-66-39.3210425.0

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