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Raihan004
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Action_model

Image Classification
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vit
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  1. README.md +12 -38
  2. model.safetensors +1 -1
  3. runs/Apr16_07-14-49_7b4e89625b83/events.out.tfevents.1713251886.7b4e89625b83.34.0 +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_class
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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: 0.799047619047619
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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_model
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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_class dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6551
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- - Accuracy: 0.7990
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  ## Model description
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@@ -59,44 +58,19 @@ The following hyperparameters were used during training:
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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: 10
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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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- | 1.1382 | 0.32 | 100 | 1.0002 | 0.7676 |
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- | 0.782 | 0.64 | 200 | 0.7673 | 0.7676 |
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- | 0.6289 | 0.96 | 300 | 0.7073 | 0.7867 |
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- | 0.5028 | 1.27 | 400 | 0.7261 | 0.7686 |
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- | 0.4746 | 1.59 | 500 | 0.7464 | 0.7619 |
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- | 0.4298 | 1.91 | 600 | 0.6551 | 0.7990 |
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- | 0.3488 | 2.23 | 700 | 0.7359 | 0.7733 |
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- | 0.266 | 2.55 | 800 | 0.8296 | 0.7514 |
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- | 0.3651 | 2.87 | 900 | 0.8661 | 0.7305 |
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- | 0.2796 | 3.18 | 1000 | 0.7188 | 0.7867 |
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- | 0.2703 | 3.5 | 1100 | 0.8422 | 0.7476 |
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- | 0.2608 | 3.82 | 1200 | 0.8207 | 0.7724 |
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- | 0.251 | 4.14 | 1300 | 1.0252 | 0.7267 |
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- | 0.2085 | 4.46 | 1400 | 1.0475 | 0.7171 |
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- | 0.1715 | 4.78 | 1500 | 0.8852 | 0.7495 |
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- | 0.2051 | 5.1 | 1600 | 0.8164 | 0.7790 |
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- | 0.1481 | 5.41 | 1700 | 0.8825 | 0.7629 |
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- | 0.177 | 5.73 | 1800 | 0.8623 | 0.7867 |
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- | 0.1607 | 6.05 | 1900 | 0.9487 | 0.7610 |
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- | 0.1273 | 6.37 | 2000 | 0.8985 | 0.7733 |
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- | 0.1609 | 6.69 | 2100 | 0.9624 | 0.7505 |
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- | 0.1583 | 7.01 | 2200 | 0.9015 | 0.7781 |
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- | 0.1178 | 7.32 | 2300 | 0.9143 | 0.7762 |
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- | 0.1175 | 7.64 | 2400 | 0.9671 | 0.7590 |
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- | 0.1257 | 7.96 | 2500 | 0.8925 | 0.7838 |
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- | 0.0939 | 8.28 | 2600 | 0.9257 | 0.7705 |
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- | 0.1238 | 8.6 | 2700 | 0.9797 | 0.7648 |
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- | 0.1219 | 8.92 | 2800 | 0.9399 | 0.7724 |
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- | 0.0985 | 9.24 | 2900 | 0.9940 | 0.7648 |
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- | 0.1069 | 9.55 | 3000 | 0.9392 | 0.7743 |
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- | 0.0589 | 9.87 | 3100 | 0.9408 | 0.78 |
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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: 0.8066666666666666
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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_model
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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: 0.6526
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+ - Accuracy: 0.8067
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  ## Model description
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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: 2
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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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+ | 1.1323 | 0.32 | 100 | 1.0434 | 0.7543 |
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+ | 0.7842 | 0.64 | 200 | 0.7772 | 0.7810 |
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+ | 0.6174 | 0.96 | 300 | 0.7121 | 0.7848 |
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+ | 0.5362 | 1.27 | 400 | 0.7486 | 0.7724 |
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+ | 0.4918 | 1.59 | 500 | 0.6675 | 0.8029 |
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+ | 0.4346 | 1.91 | 600 | 0.6526 | 0.8067 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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