Model save
Browse files- README.md +77 -0
- config.json +32 -0
- model.safetensors +3 -0
- preprocessor_config.json +22 -0
- runs/Aug22_17-26-15_95d27f699f23/events.out.tfevents.1724347638.95d27f699f23.377.0 +3 -0
- training_args.bin +3 -0
README.md
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---
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license: apache-2.0
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base_model: dima806/deepfake_vs_real_image_detection
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tags:
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- generated_from_trainer
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datasets:
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- imagefolder
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metrics:
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- accuracy
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model-index:
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- name: realFake-food
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results:
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- task:
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name: Image Classification
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type: image-classification
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dataset:
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name: imagefolder
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type: imagefolder
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config: default
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split: train
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args: default
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.910958904109589
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# realFake-food
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This model is a fine-tuned version of [dima806/deepfake_vs_real_image_detection](https://huggingface.co/dima806/deepfake_vs_real_image_detection) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2562
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- Accuracy: 0.9110
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0002
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- train_batch_size: 16
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 4
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:------:|:----:|:---------------:|:--------:|
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| 0.4947 | 1.9231 | 100 | 0.4738 | 0.7945 |
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| 0.151 | 3.8462 | 200 | 0.2562 | 0.9110 |
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### Framework versions
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- Transformers 4.42.4
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- Pytorch 2.3.1+cu121
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- Datasets 2.21.0
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- Tokenizers 0.19.1
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config.json
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{
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"_name_or_path": "dima806/deepfake_vs_real_image_detection",
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"architectures": [
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"ViTForImageClassification"
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],
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"attention_probs_dropout_prob": 0.0,
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"encoder_stride": 16,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.0,
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"hidden_size": 768,
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"id2label": {
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"0": "AiArtData",
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"1": "RealArt"
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},
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"image_size": 224,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"AiArtData": "0",
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"RealArt": "1"
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},
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"layer_norm_eps": 1e-12,
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"model_type": "vit",
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"num_attention_heads": 12,
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"num_channels": 3,
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"num_hidden_layers": 12,
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"patch_size": 16,
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"problem_type": "single_label_classification",
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"qkv_bias": true,
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"torch_dtype": "float32",
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"transformers_version": "4.42.4"
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:031f1a862fb7f92b509c5a50d7dbbbc0c11c8a254d8b92e00f29aa086a11a06a
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size 343223968
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preprocessor_config.json
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{
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"do_normalize": true,
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"do_rescale": true,
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"do_resize": true,
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"image_mean": [
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0.5,
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0.5,
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0.5
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],
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"image_processor_type": "ViTFeatureExtractor",
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"image_std": [
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0.5,
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0.5,
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0.5
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],
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"resample": 2,
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"rescale_factor": 0.00392156862745098,
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"size": {
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"height": 224,
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"width": 224
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}
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}
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runs/Aug22_17-26-15_95d27f699f23/events.out.tfevents.1724347638.95d27f699f23.377.0
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version https://git-lfs.github.com/spec/v1
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oid sha256:b3721c6372628dc1153d328a27af6fa9e79356026d9e1d4d430d7a9a32fbe2f6
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size 10083
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:ca547214c1d3308687d8a8476b71cdf8a1a82a13e251454381cb35a1ddd9eb31
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size 5112
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