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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 +69 -11
  2. model.safetensors +1 -1
  3. runs/Apr17_07-35-21_780228e9e9f6/events.out.tfevents.1713339401.780228e9e9f6.33.0 +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: 0.8095238095238095
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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: 0.7479
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- - Accuracy: 0.8095
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  ## Model description
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@@ -54,21 +53,80 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 0.0001
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- - train_batch_size: 32
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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: 1
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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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- | 1.1778 | 0.32 | 100 | 1.0651 | 0.78 |
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- | 0.8527 | 0.64 | 200 | 0.7874 | 0.8133 |
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- | 0.7114 | 0.96 | 300 | 0.7479 | 0.8095 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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: 0.7695238095238095
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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: 1.1418
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+ - Accuracy: 0.7695
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 0.0001
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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: 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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+ | 1.3203 | 0.16 | 100 | 1.1810 | 0.7448 |
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+ | 0.998 | 0.32 | 200 | 0.8925 | 0.7705 |
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+ | 0.765 | 0.48 | 300 | 0.8199 | 0.7638 |
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+ | 0.6521 | 0.64 | 400 | 0.8276 | 0.7371 |
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+ | 0.7612 | 0.8 | 500 | 0.8631 | 0.7210 |
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+ | 0.5894 | 0.96 | 600 | 0.8176 | 0.7476 |
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+ | 0.5381 | 1.11 | 700 | 0.7965 | 0.7524 |
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+ | 0.4066 | 1.27 | 800 | 0.8102 | 0.7486 |
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+ | 0.4825 | 1.43 | 900 | 0.7498 | 0.7743 |
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+ | 0.4955 | 1.59 | 1000 | 0.9752 | 0.7019 |
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+ | 0.3945 | 1.75 | 1100 | 0.8150 | 0.7381 |
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+ | 0.4142 | 1.91 | 1200 | 0.7953 | 0.7610 |
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+ | 0.3915 | 2.07 | 1300 | 0.8141 | 0.7638 |
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+ | 0.3937 | 2.23 | 1400 | 0.7882 | 0.7705 |
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+ | 0.3144 | 2.39 | 1500 | 0.8657 | 0.7514 |
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+ | 0.3143 | 2.55 | 1600 | 1.0562 | 0.7086 |
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+ | 0.3884 | 2.71 | 1700 | 1.0502 | 0.7162 |
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+ | 0.3472 | 2.87 | 1800 | 0.8506 | 0.7571 |
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+ | 0.2545 | 3.03 | 1900 | 1.0029 | 0.7210 |
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+ | 0.2213 | 3.18 | 2000 | 0.8099 | 0.7933 |
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+ | 0.3429 | 3.34 | 2100 | 0.9166 | 0.7467 |
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+ | 0.3478 | 3.5 | 2200 | 0.9202 | 0.7562 |
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+ | 0.2247 | 3.66 | 2300 | 0.9859 | 0.7638 |
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+ | 0.2873 | 3.82 | 2400 | 1.0161 | 0.7390 |
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+ | 0.2815 | 3.98 | 2500 | 0.9631 | 0.7590 |
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+ | 0.1706 | 4.14 | 2600 | 0.9996 | 0.7419 |
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+ | 0.1709 | 4.3 | 2700 | 1.1969 | 0.7029 |
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+ | 0.2847 | 4.46 | 2800 | 1.0896 | 0.7276 |
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+ | 0.286 | 4.62 | 2900 | 0.9894 | 0.7629 |
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+ | 0.2066 | 4.78 | 3000 | 1.0704 | 0.7486 |
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+ | 0.1579 | 4.94 | 3100 | 0.9728 | 0.7810 |
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+ | 0.1716 | 5.1 | 3200 | 1.1834 | 0.7124 |
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+ | 0.1584 | 5.25 | 3300 | 1.0278 | 0.7524 |
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+ | 0.1419 | 5.41 | 3400 | 1.1342 | 0.7371 |
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+ | 0.2002 | 5.57 | 3500 | 1.1519 | 0.7324 |
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+ | 0.1987 | 5.73 | 3600 | 1.0742 | 0.7562 |
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+ | 0.1207 | 5.89 | 3700 | 1.1579 | 0.7381 |
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+ | 0.1403 | 6.05 | 3800 | 1.1007 | 0.7305 |
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+ | 0.1569 | 6.21 | 3900 | 1.1128 | 0.7467 |
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+ | 0.1763 | 6.37 | 4000 | 1.0720 | 0.7524 |
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+ | 0.2426 | 6.53 | 4100 | 1.1484 | 0.7248 |
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+ | 0.1434 | 6.69 | 4200 | 1.1790 | 0.7343 |
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+ | 0.2191 | 6.85 | 4300 | 1.1169 | 0.7486 |
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+ | 0.2062 | 7.01 | 4400 | 1.1300 | 0.7610 |
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+ | 0.1495 | 7.17 | 4500 | 1.1477 | 0.7495 |
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+ | 0.1261 | 7.32 | 4600 | 1.0891 | 0.7657 |
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+ | 0.12 | 7.48 | 4700 | 1.1359 | 0.76 |
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+ | 0.1396 | 7.64 | 4800 | 1.1230 | 0.7410 |
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+ | 0.0728 | 7.8 | 4900 | 1.1210 | 0.7552 |
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+ | 0.175 | 7.96 | 5000 | 1.1204 | 0.7505 |
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+ | 0.1214 | 8.12 | 5100 | 1.1064 | 0.7543 |
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+ | 0.1218 | 8.28 | 5200 | 1.0232 | 0.7771 |
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+ | 0.1556 | 8.44 | 5300 | 1.0489 | 0.7771 |
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+ | 0.1019 | 8.6 | 5400 | 1.0916 | 0.7752 |
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+ | 0.1446 | 8.76 | 5500 | 1.1856 | 0.7505 |
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+ | 0.1348 | 8.92 | 5600 | 1.1380 | 0.7638 |
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+ | 0.1402 | 9.08 | 5700 | 1.1233 | 0.7695 |
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+ | 0.1075 | 9.24 | 5800 | 1.1472 | 0.7629 |
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+ | 0.0991 | 9.39 | 5900 | 1.1530 | 0.7648 |
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+ | 0.081 | 9.55 | 6000 | 1.1586 | 0.7629 |
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+ | 0.0724 | 9.71 | 6100 | 1.1591 | 0.7676 |
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+ | 0.0399 | 9.87 | 6200 | 1.1418 | 0.7695 |
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  ### Framework versions
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