Model save

README.md

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+---
+base_model: openai/clip-vit-base-patch32
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: ktp-spoof-clip
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: validation
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 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. -->
+
+# ktp-spoof-clip
+
+This model is a fine-tuned version of [openai/clip-vit-base-patch32](https://huggingface.co/openai/clip-vit-base-patch32) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0026
+- Accuracy: 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: 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: 20
+
+### Training results
+
+| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
+|:-------------:|:-------:|:----:|:---------------:|:--------:|
+| No log        | 0.8889  | 4    | 0.5977          | 0.7794   |
+| No log        | 2.0     | 9    | 0.4052          | 0.7941   |
+| 0.662         | 2.8889  | 13   | 0.9644          | 0.5      |
+| 0.662         | 4.0     | 18   | 0.2191          | 0.9265   |
+| 0.5454        | 4.8889  | 22   | 0.1040          | 0.9706   |
+| 0.5454        | 6.0     | 27   | 0.0587          | 0.9853   |
+| 0.1982        | 6.8889  | 31   | 0.0637          | 0.9853   |
+| 0.1982        | 8.0     | 36   | 0.0255          | 1.0      |
+| 0.1826        | 8.8889  | 40   | 0.0617          | 0.9559   |
+| 0.1826        | 10.0    | 45   | 0.0519          | 0.9853   |
+| 0.1826        | 10.8889 | 49   | 0.0369          | 0.9706   |
+| 0.0996        | 12.0    | 54   | 0.0348          | 0.9853   |
+| 0.0996        | 12.8889 | 58   | 0.1207          | 0.9412   |
+| 0.0829        | 14.0    | 63   | 0.0158          | 0.9853   |
+| 0.0829        | 14.8889 | 67   | 0.0577          | 0.9706   |
+| 0.0348        | 16.0    | 72   | 0.0129          | 0.9853   |
+| 0.0348        | 16.8889 | 76   | 0.0052          | 1.0      |
+| 0.0103        | 17.7778 | 80   | 0.0026          | 1.0      |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.1.2
+- Datasets 2.19.2
+- Tokenizers 0.19.1

model.safetensors

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