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FacialConfidence

Image Classification
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vit
Generated from Trainer
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  1. README.md +133 -0
  2. all_results.json +8 -0
  3. config.json +32 -0
  4. eval_results.json +8 -0
  5. model.safetensors +3 -0
  6. preprocessor_config.json +22 -0
  7. runs/Oct29_19-12-50_8f2f0942f124/events.out.tfevents.1730233923.8f2f0942f124.1836.1 +3 -0
  8. 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: google/vit-base-patch16-224-in21k
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+ tags:
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+ - image-classification
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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: vit-base-beans
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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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+ # vit-base-beans
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+
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+ This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the FacialConfidence dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2560
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+ - Accuracy: 0.8970
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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: 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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+
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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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+ | 0.6103 | 0.0557 | 100 | 0.5715 | 0.7310 |
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+ | 0.554 | 0.1114 | 200 | 0.5337 | 0.7194 |
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+ | 0.4275 | 0.1671 | 300 | 0.5142 | 0.7549 |
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+ | 0.5831 | 0.2228 | 400 | 0.5570 | 0.7345 |
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+ | 0.5804 | 0.2786 | 500 | 0.4909 | 0.7660 |
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+ | 0.5652 | 0.3343 | 600 | 0.4956 | 0.7764 |
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+ | 0.4513 | 0.3900 | 700 | 0.4294 | 0.7972 |
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+ | 0.4217 | 0.4457 | 800 | 0.4619 | 0.7924 |
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+ | 0.435 | 0.5014 | 900 | 0.4563 | 0.7901 |
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+ | 0.3943 | 0.5571 | 1000 | 0.4324 | 0.7917 |
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+ | 0.4136 | 0.6128 | 1100 | 0.4131 | 0.8110 |
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+ | 0.3302 | 0.6685 | 1200 | 0.4516 | 0.8054 |
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+ | 0.4945 | 0.7242 | 1300 | 0.4135 | 0.8164 |
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+ | 0.3729 | 0.7799 | 1400 | 0.4010 | 0.8139 |
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+ | 0.4865 | 0.8357 | 1500 | 0.4145 | 0.8174 |
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+ | 0.4011 | 0.8914 | 1600 | 0.4098 | 0.8112 |
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+ | 0.4287 | 0.9471 | 1700 | 0.3914 | 0.8181 |
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+ | 0.3644 | 1.0028 | 1800 | 0.3948 | 0.8188 |
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+ | 0.3768 | 1.0585 | 1900 | 0.4044 | 0.8266 |
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+ | 0.383 | 1.1142 | 2000 | 0.4363 | 0.8064 |
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+ | 0.4011 | 1.1699 | 2100 | 0.4424 | 0.8025 |
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+ | 0.4079 | 1.2256 | 2200 | 0.4384 | 0.7853 |
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+ | 0.2791 | 1.2813 | 2300 | 0.4491 | 0.8089 |
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+ | 0.3159 | 1.3370 | 2400 | 0.3863 | 0.8274 |
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+ | 0.4306 | 1.3928 | 2500 | 0.3944 | 0.8158 |
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+ | 0.3386 | 1.4485 | 2600 | 0.3835 | 0.8305 |
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+ | 0.395 | 1.5042 | 2700 | 0.3812 | 0.8261 |
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+ | 0.3041 | 1.5599 | 2800 | 0.3736 | 0.8312 |
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+ | 0.3365 | 1.6156 | 2900 | 0.4420 | 0.8097 |
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+ | 0.3697 | 1.6713 | 3000 | 0.3808 | 0.8353 |
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+ | 0.3661 | 1.7270 | 3100 | 0.4046 | 0.8084 |
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+ | 0.3208 | 1.7827 | 3200 | 0.4042 | 0.8328 |
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+ | 0.3511 | 1.8384 | 3300 | 0.4113 | 0.8192 |
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+ | 0.3246 | 1.8942 | 3400 | 0.3611 | 0.8377 |
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+ | 0.3616 | 1.9499 | 3500 | 0.4207 | 0.8231 |
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+ | 0.2726 | 2.0056 | 3600 | 0.3650 | 0.8342 |
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+ | 0.1879 | 2.0613 | 3700 | 0.4334 | 0.8359 |
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+ | 0.2981 | 2.1170 | 3800 | 0.3657 | 0.8435 |
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+ | 0.227 | 2.1727 | 3900 | 0.3948 | 0.8399 |
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+ | 0.3184 | 2.2284 | 4000 | 0.4229 | 0.8377 |
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+ | 0.2391 | 2.2841 | 4100 | 0.3824 | 0.8405 |
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+ | 0.2019 | 2.3398 | 4200 | 0.4628 | 0.8345 |
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+ | 0.1931 | 2.3955 | 4300 | 0.3848 | 0.8448 |
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+ | 0.238 | 2.4513 | 4400 | 0.3948 | 0.8398 |
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+ | 0.2633 | 2.5070 | 4500 | 0.3779 | 0.8440 |
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+ | 0.1829 | 2.5627 | 4600 | 0.3901 | 0.8455 |
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+ | 0.2286 | 2.6184 | 4700 | 0.3797 | 0.8481 |
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+ | 0.2123 | 2.6741 | 4800 | 0.4203 | 0.8502 |
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+ | 0.266 | 2.7298 | 4900 | 0.4073 | 0.8455 |
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+ | 0.1768 | 2.7855 | 5000 | 0.3750 | 0.8498 |
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+ | 0.1659 | 2.8412 | 5100 | 0.3906 | 0.8427 |
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+ | 0.1644 | 2.8969 | 5200 | 0.3833 | 0.8466 |
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+ | 0.241 | 2.9526 | 5300 | 0.4071 | 0.8476 |
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+ | 0.16 | 3.0084 | 5400 | 0.3691 | 0.8530 |
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+ | 0.0788 | 3.0641 | 5500 | 0.4656 | 0.8514 |
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+ | 0.1244 | 3.1198 | 5600 | 0.4990 | 0.8484 |
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+ | 0.1423 | 3.1755 | 5700 | 0.5219 | 0.8475 |
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+ | 0.1279 | 3.2312 | 5800 | 0.5687 | 0.8515 |
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+ | 0.0974 | 3.2869 | 5900 | 0.5386 | 0.8458 |
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+ | 0.065 | 3.3426 | 6000 | 0.5215 | 0.8454 |
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+ | 0.0497 | 3.3983 | 6100 | 0.5161 | 0.8483 |
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+ | 0.1871 | 3.4540 | 6200 | 0.5148 | 0.8523 |
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+ | 0.0891 | 3.5097 | 6300 | 0.4915 | 0.8527 |
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+ | 0.1375 | 3.5655 | 6400 | 0.5067 | 0.8509 |
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+ | 0.1333 | 3.6212 | 6500 | 0.5272 | 0.8532 |
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+ | 0.2635 | 3.6769 | 6600 | 0.5170 | 0.8516 |
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+ | 0.0375 | 3.7326 | 6700 | 0.5148 | 0.8534 |
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+ | 0.1286 | 3.7883 | 6800 | 0.4945 | 0.8543 |
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+ | 0.091 | 3.8440 | 6900 | 0.4948 | 0.8540 |
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+ | 0.1088 | 3.8997 | 7000 | 0.4985 | 0.8532 |
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+ | 0.0598 | 3.9554 | 7100 | 0.4969 | 0.8514 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.44.2
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+ - Pytorch 2.5.0+cu121
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+ - Datasets 3.0.2
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+ - Tokenizers 0.19.1
all_results.json ADDED
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+ {
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+ "epoch": 4.0,
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+ "eval_accuracy": 0.8969589298777302,
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+ "eval_loss": 0.2560151517391205,
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+ "eval_runtime": 138.2305,
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+ "eval_samples_per_second": 207.675,
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+ "eval_steps_per_second": 25.964
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+ }
config.json ADDED
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+ {
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+ "_name_or_path": "google/vit-base-patch16-224-in21k",
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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": "confident",
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+ "1": "unconfident"
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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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+ "confident": "0",
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+ "unconfident": "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": "4.44.2"
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+ }
eval_results.json ADDED
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+ {
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+ "epoch": 4.0,
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+ "eval_accuracy": 0.8969589298777302,
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+ "eval_loss": 0.2560151517391205,
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+ "eval_runtime": 138.2305,
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+ "eval_samples_per_second": 207.675,
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+ "eval_steps_per_second": 25.964
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+ }
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