songthienll/ai_image_generator_detect

README.md

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+---
+library_name: transformers
+license: other
+base_model: apple/mobilevit-small
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: mobilevit_ai_real_classifier
+  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: 0.93875
+---
+
+<!-- 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. -->
+
+# mobilevit_ai_real_classifier
+
+This model is a fine-tuned version of [apple/mobilevit-small](https://huggingface.co/apple/mobilevit-small) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1560
+- Accuracy: 0.9387
+
+## 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: 0.0003
+- train_batch_size: 64
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.2392        | 1.0   | 219  | 0.2392          | 0.9115   |
+| 0.1804        | 2.0   | 438  | 0.1905          | 0.9295   |
+| 0.1611        | 3.0   | 657  | 0.1772          | 0.935    |
+| 0.1225        | 4.0   | 876  | 0.1784          | 0.938    |
+| 0.0955        | 5.0   | 1095 | 0.2000          | 0.9325   |
+
+
+### Framework versions
+
+- Transformers 4.51.3
+- Pytorch 2.6.0+cu124
+- Datasets 3.6.0
+- Tokenizers 0.21.1

config.json

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+{
+  "architectures": [
+    "MobileViTForImageClassification"
+  ],
+  "aspp_dropout_prob": 0.1,
+  "aspp_out_channels": 256,
+  "atrous_rates": [
+    6,
+    12,
+    18
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "classifier_dropout_prob": 0.1,
+  "conv_kernel_size": 3,
+  "expand_ratio": 4.0,
+  "hidden_act": "silu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_sizes": [
+    144,
+    192,
+    240
+  ],
+  "id2label": {
+    "0": "fake",
+    "1": "real"
+  },
+  "image_size": 256,
+  "initializer_range": 0.02,
+  "label2id": {
+    "fake": 0,
+    "real": 1
+  },
+  "layer_norm_eps": 1e-05,
+  "mlp_ratio": 2.0,
+  "model_type": "mobilevit",
+  "neck_hidden_sizes": [
+    16,
+    32,
+    64,
+    96,
+    128,
+    160,
+    640
+  ],
+  "num_attention_heads": 4,
+  "num_channels": 3,
+  "output_stride": 32,
+  "patch_size": 2,
+  "problem_type": "single_label_classification",
+  "qkv_bias": true,
+  "semantic_loss_ignore_index": 255,
+  "torch_dtype": "float32",
+  "transformers_version": "4.51.3"
+}

model.safetensors

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+oid sha256:d397284d44f0f8e38d09f81dcb5ed7eac05f6298ef0d7d518f304d60c699135a
+size 19851560

training_args.bin

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+oid sha256:22b9609afa5564f86bdf12a345dfccb536bf900d30bdcd4e7119cf7f5b654997
+size 5304