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Action_all_10_class

Image Classification
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  1. README.md +32 -34
  2. model.safetensors +1 -1
  3. runs/May05_18-32-14_a7a783b06297/events.out.tfevents.1714933935.a7a783b06297.35.0 +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -2,7 +2,6 @@
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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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  datasets:
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  - imagefolder
@@ -15,7 +14,7 @@ model-index:
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  name: Image Classification
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  type: image-classification
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  dataset:
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- name: Action_small_dataset
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  type: imagefolder
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  config: default
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  split: train
@@ -23,7 +22,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.8699386503067484
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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
@@ -31,10 +30,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # Action_all_10_class
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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 Action_small_dataset dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4618
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- - Accuracy: 0.8699
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  ## Model description
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@@ -66,34 +65,33 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 1.1996 | 0.35 | 100 | 1.0635 | 0.7730 |
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- | 1.0335 | 0.69 | 200 | 0.8392 | 0.7718 |
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- | 0.6279 | 1.04 | 300 | 0.6463 | 0.8294 |
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- | 0.8633 | 1.38 | 400 | 0.7172 | 0.7926 |
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- | 0.5851 | 1.73 | 500 | 0.5858 | 0.8380 |
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- | 0.5305 | 2.08 | 600 | 0.5780 | 0.8356 |
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- | 0.5511 | 2.42 | 700 | 0.5313 | 0.8393 |
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- | 0.4657 | 2.77 | 800 | 0.5443 | 0.8368 |
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- | 0.3615 | 3.11 | 900 | 0.5038 | 0.8429 |
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- | 0.5301 | 3.46 | 1000 | 0.5101 | 0.8503 |
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- | 0.4108 | 3.81 | 1100 | 0.5212 | 0.8479 |
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- | 0.4223 | 4.15 | 1200 | 0.5328 | 0.8429 |
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- | 0.3877 | 4.5 | 1300 | 0.5815 | 0.8294 |
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- | 0.3879 | 4.84 | 1400 | 0.5151 | 0.8503 |
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- | 0.2797 | 5.19 | 1500 | 0.5160 | 0.8564 |
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- | 0.2628 | 5.54 | 1600 | 0.4618 | 0.8699 |
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- | 0.3404 | 5.88 | 1700 | 0.4903 | 0.8675 |
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- | 0.3033 | 6.23 | 1800 | 0.4861 | 0.8663 |
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- | 0.214 | 6.57 | 1900 | 0.4853 | 0.8687 |
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- | 0.2763 | 6.92 | 2000 | 0.4705 | 0.8736 |
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- | 0.3009 | 7.27 | 2100 | 0.4723 | 0.8626 |
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- | 0.1543 | 7.61 | 2200 | 0.4983 | 0.8638 |
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- | 0.2407 | 7.96 | 2300 | 0.4742 | 0.8650 |
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- | 0.2679 | 8.3 | 2400 | 0.4935 | 0.8724 |
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- | 0.1508 | 8.65 | 2500 | 0.4826 | 0.8675 |
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- | 0.2129 | 9.0 | 2600 | 0.4981 | 0.8712 |
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- | 0.1131 | 9.34 | 2700 | 0.4718 | 0.8712 |
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- | 0.2144 | 9.69 | 2800 | 0.4745 | 0.8712 |
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  ### Framework versions
 
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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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  - generated_from_trainer
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  datasets:
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  - imagefolder
 
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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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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.8767249310027599
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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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  # Action_all_10_class
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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 imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.4467
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+ - Accuracy: 0.8767
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 1.3206 | 0.37 | 100 | 1.1438 | 0.7387 |
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+ | 0.9631 | 0.74 | 200 | 0.8203 | 0.7893 |
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+ | 0.6572 | 1.1 | 300 | 0.6730 | 0.8105 |
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+ | 0.629 | 1.47 | 400 | 0.5897 | 0.8335 |
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+ | 0.722 | 1.84 | 500 | 0.5345 | 0.8491 |
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+ | 0.5069 | 2.21 | 600 | 0.5244 | 0.8473 |
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+ | 0.5711 | 2.57 | 700 | 0.4997 | 0.8574 |
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+ | 0.5162 | 2.94 | 800 | 0.5146 | 0.8473 |
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+ | 0.444 | 3.31 | 900 | 0.4583 | 0.8528 |
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+ | 0.3708 | 3.68 | 1000 | 0.5439 | 0.8372 |
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+ | 0.4273 | 4.04 | 1100 | 0.4629 | 0.8602 |
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+ | 0.3491 | 4.41 | 1200 | 0.4811 | 0.8592 |
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+ | 0.3507 | 4.78 | 1300 | 0.4860 | 0.8519 |
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+ | 0.2684 | 5.15 | 1400 | 0.4626 | 0.8629 |
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+ | 0.294 | 5.51 | 1500 | 0.4679 | 0.8592 |
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+ | 0.3686 | 5.88 | 1600 | 0.4999 | 0.8592 |
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+ | 0.3195 | 6.25 | 1700 | 0.4460 | 0.8703 |
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+ | 0.1949 | 6.62 | 1800 | 0.4375 | 0.8786 |
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+ | 0.2524 | 6.99 | 1900 | 0.4394 | 0.8795 |
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+ | 0.1885 | 7.35 | 2000 | 0.4883 | 0.8648 |
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+ | 0.2804 | 7.72 | 2100 | 0.4509 | 0.8740 |
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+ | 0.2532 | 8.09 | 2200 | 0.4744 | 0.8629 |
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+ | 0.2038 | 8.46 | 2300 | 0.4631 | 0.8666 |
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+ | 0.3046 | 8.82 | 2400 | 0.4486 | 0.8712 |
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+ | 0.2271 | 9.19 | 2500 | 0.4655 | 0.8740 |
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+ | 0.2719 | 9.56 | 2600 | 0.4518 | 0.8758 |
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+ | 0.1563 | 9.93 | 2700 | 0.4467 | 0.8767 |
 
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  ### Framework versions
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