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finetuned_video_model

Image Classification
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vit
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DotCheck/Dotengine

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  1. README.md +90 -0
  2. config.json +33 -0
  3. model.safetensors +3 -0
  4. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: DotCheck/finetuned_model
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: finetuned_video_model
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+ results: []
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+ ---
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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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+
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+ # finetuned_video_model
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+
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+ This model is a fine-tuned version of [DotCheck/finetuned_model](https://huggingface.co/DotCheck/finetuned_model) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0712
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+ - Accuracy: 0.9821
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 1e-05
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+ - train_batch_size: 512
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+ - eval_batch_size: 512
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+ - seed: 42
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - num_epochs: 30
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 14 | 0.1532 | 0.9615 |
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+ | No log | 2.0 | 28 | 0.1363 | 0.9615 |
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+ | No log | 3.0 | 42 | 0.1180 | 0.9654 |
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+ | No log | 4.0 | 56 | 0.0998 | 0.9692 |
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+ | No log | 5.0 | 70 | 0.0862 | 0.9692 |
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+ | No log | 6.0 | 84 | 0.0808 | 0.9769 |
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+ | No log | 7.0 | 98 | 0.0737 | 0.9782 |
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+ | No log | 8.0 | 112 | 0.0677 | 0.9821 |
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+ | No log | 9.0 | 126 | 0.0685 | 0.9821 |
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+ | No log | 10.0 | 140 | 0.0704 | 0.9821 |
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+ | No log | 11.0 | 154 | 0.0676 | 0.9821 |
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+ | No log | 12.0 | 168 | 0.0653 | 0.9821 |
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+ | No log | 13.0 | 182 | 0.0679 | 0.9833 |
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+ | No log | 14.0 | 196 | 0.0674 | 0.9833 |
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+ | No log | 15.0 | 210 | 0.0673 | 0.9833 |
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+ | No log | 16.0 | 224 | 0.0692 | 0.9821 |
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+ | No log | 17.0 | 238 | 0.0676 | 0.9833 |
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+ | No log | 18.0 | 252 | 0.0691 | 0.9833 |
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+ | No log | 19.0 | 266 | 0.0699 | 0.9821 |
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+ | No log | 20.0 | 280 | 0.0688 | 0.9833 |
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+ | No log | 21.0 | 294 | 0.0694 | 0.9833 |
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+ | No log | 22.0 | 308 | 0.0707 | 0.9821 |
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+ | No log | 23.0 | 322 | 0.0707 | 0.9821 |
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+ | No log | 24.0 | 336 | 0.0706 | 0.9821 |
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+ | No log | 25.0 | 350 | 0.0710 | 0.9821 |
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+ | No log | 26.0 | 364 | 0.0711 | 0.9821 |
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+ | No log | 27.0 | 378 | 0.0710 | 0.9821 |
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+ | No log | 28.0 | 392 | 0.0710 | 0.9821 |
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+ | No log | 29.0 | 406 | 0.0712 | 0.9821 |
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+ | No log | 30.0 | 420 | 0.0712 | 0.9821 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.54.1
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+ - Pytorch 2.6.0+cu124
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+ - Datasets 4.0.0
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+ - Tokenizers 0.21.4
config.json ADDED
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+ {
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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": "REAL",
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+ "1": "FAKE"
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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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+ "FAKE": 1,
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+ "REAL": 0
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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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+ "pooler_act": "tanh",
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+ "pooler_output_size": 768,
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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": "4.54.1"
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+ }
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