End of training

README.md

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+---
+license: apache-2.0
+base_model: google/vit-base-patch16-384
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: DeepFake-image-detection-ViT-384
+  results: []
+---
+
+<!-- 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. -->
+
+# DeepFake-image-detection-ViT-384
+
+This model is a fine-tuned version of [google/vit-base-patch16-384](https://huggingface.co/google/vit-base-patch16-384) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0272
+- Accuracy: 0.9911
+
+## 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: 3e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 256
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 2.5
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
+|:-------------:|:------:|:----:|:---------------:|:--------:|
+| 0.0037        | 0.9984 | 546  | 0.0272          | 0.9911   |
+| 0.0006        | 1.9986 | 1093 | 0.1121          | 0.9644   |
+| 0.0002        | 2.496  | 1365 | 0.1357          | 0.9582   |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.1.2
+- Datasets 2.19.2
+- Tokenizers 0.19.1

all_results.json

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+{
+    "epoch": 2.496,
+    "eval_accuracy": 0.9910666666666667,
+    "eval_loss": 0.027157384902238846,
+    "eval_runtime": 543.4232,
+    "eval_samples_per_second": 55.206,
+    "eval_steps_per_second": 1.726
+}

eval_results.json

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+{
+    "epoch": 2.496,
+    "eval_accuracy": 0.9910666666666667,
+    "eval_loss": 0.027157384902238846,
+    "eval_runtime": 543.4232,
+    "eval_samples_per_second": 55.206,
+    "eval_steps_per_second": 1.726
+}

model.safetensors

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