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Action_all_10_class

Image Classification
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  1. README.md +32 -33
  2. model.safetensors +1 -1
  3. runs/May07_14-51-35_d582cceb3b6a/events.out.tfevents.1715093496.d582cceb3b6a.34.0 +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: 0.8752556237218814
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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: 0.4228
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- - Accuracy: 0.8753
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  ## Model description
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@@ -66,33 +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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- | 1.3076 | 0.36 | 100 | 1.1509 | 0.7260 |
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- | 0.9605 | 0.72 | 200 | 0.7632 | 0.8057 |
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- | 0.7508 | 1.08 | 300 | 0.6995 | 0.8006 |
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- | 0.7542 | 1.43 | 400 | 0.5710 | 0.8364 |
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- | 0.6945 | 1.79 | 500 | 0.5104 | 0.8589 |
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- | 0.5218 | 2.15 | 600 | 0.5389 | 0.8344 |
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- | 0.5365 | 2.51 | 700 | 0.5035 | 0.8466 |
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- | 0.5564 | 2.87 | 800 | 0.4817 | 0.8476 |
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- | 0.4597 | 3.23 | 900 | 0.4690 | 0.8599 |
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- | 0.3516 | 3.58 | 1000 | 0.4921 | 0.8507 |
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- | 0.3741 | 3.94 | 1100 | 0.4820 | 0.8569 |
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- | 0.4169 | 4.3 | 1200 | 0.4730 | 0.8528 |
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- | 0.5131 | 4.66 | 1300 | 0.4482 | 0.8681 |
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- | 0.3673 | 5.02 | 1400 | 0.4228 | 0.8753 |
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- | 0.3722 | 5.38 | 1500 | 0.4820 | 0.8599 |
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- | 0.3005 | 5.73 | 1600 | 0.4456 | 0.8732 |
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- | 0.2183 | 6.09 | 1700 | 0.4255 | 0.8753 |
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- | 0.2546 | 6.45 | 1800 | 0.4644 | 0.8681 |
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- | 0.3798 | 6.81 | 1900 | 0.4918 | 0.8528 |
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- | 0.2851 | 7.17 | 2000 | 0.4574 | 0.8661 |
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- | 0.3897 | 7.53 | 2100 | 0.4750 | 0.8650 |
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- | 0.2879 | 7.89 | 2200 | 0.4739 | 0.8640 |
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- | 0.1619 | 8.24 | 2300 | 0.4645 | 0.8701 |
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- | 0.1791 | 8.6 | 2400 | 0.4636 | 0.8671 |
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- | 0.1697 | 8.96 | 2500 | 0.4716 | 0.8640 |
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- | 0.1608 | 9.32 | 2600 | 0.4681 | 0.8742 |
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- | 0.2105 | 9.68 | 2700 | 0.4719 | 0.8722 |
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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: 0.8680981595092024
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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: 0.4765
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+ - Accuracy: 0.8681
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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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+ | 1.2411 | 0.36 | 100 | 1.1517 | 0.7546 |
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+ | 0.8932 | 0.72 | 200 | 0.7856 | 0.7975 |
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+ | 0.6907 | 1.08 | 300 | 0.6636 | 0.8221 |
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+ | 0.5841 | 1.43 | 400 | 0.6388 | 0.8160 |
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+ | 0.5425 | 1.79 | 500 | 0.5871 | 0.8436 |
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+ | 0.5929 | 2.15 | 600 | 0.5646 | 0.8211 |
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+ | 0.4406 | 2.51 | 700 | 0.5439 | 0.8405 |
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+ | 0.4541 | 2.87 | 800 | 0.5318 | 0.8415 |
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+ | 0.3835 | 3.23 | 900 | 0.5225 | 0.8344 |
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+ | 0.3924 | 3.58 | 1000 | 0.5515 | 0.8303 |
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+ | 0.5741 | 3.94 | 1100 | 0.5519 | 0.8252 |
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+ | 0.3991 | 4.3 | 1200 | 0.4990 | 0.8446 |
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+ | 0.4732 | 4.66 | 1300 | 0.5336 | 0.8303 |
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+ | 0.3324 | 5.02 | 1400 | 0.5351 | 0.8282 |
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+ | 0.3433 | 5.38 | 1500 | 0.4725 | 0.8517 |
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+ | 0.2187 | 5.73 | 1600 | 0.5042 | 0.8466 |
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+ | 0.2952 | 6.09 | 1700 | 0.5240 | 0.8548 |
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+ | 0.2687 | 6.45 | 1800 | 0.5523 | 0.8364 |
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+ | 0.3111 | 6.81 | 1900 | 0.5304 | 0.8497 |
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+ | 0.2431 | 7.17 | 2000 | 0.5104 | 0.8569 |
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+ | 0.3265 | 7.53 | 2100 | 0.5085 | 0.8691 |
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+ | 0.2595 | 7.89 | 2200 | 0.5015 | 0.8569 |
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+ | 0.1825 | 8.24 | 2300 | 0.4920 | 0.8620 |
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+ | 0.2602 | 8.6 | 2400 | 0.5016 | 0.8620 |
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+ | 0.2628 | 8.96 | 2500 | 0.4746 | 0.8681 |
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+ | 0.1024 | 9.32 | 2600 | 0.4818 | 0.8691 |
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+ | 0.1468 | 9.68 | 2700 | 0.4765 | 0.8681 |
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  ### Framework versions
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