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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 +31 -32
  2. model.safetensors +1 -1
  3. runs/May01_07-50-39_5c48e9aaec37/events.out.tfevents.1714570909.5c48e9aaec37.34.1 +2 -2
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: 0.8541300527240774
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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: 0.4922
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- - Accuracy: 0.8541
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  ## Model description
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@@ -66,32 +65,32 @@ 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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- | 1.2738 | 0.37 | 100 | 1.1306 | 0.7346 |
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- | 0.9277 | 0.75 | 200 | 0.8469 | 0.7645 |
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- | 0.9232 | 1.12 | 300 | 0.7195 | 0.7891 |
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- | 0.7631 | 1.49 | 400 | 0.6575 | 0.8172 |
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- | 0.6677 | 1.87 | 500 | 0.5807 | 0.8348 |
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- | 0.5063 | 2.24 | 600 | 0.5663 | 0.8436 |
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- | 0.5071 | 2.61 | 700 | 0.5481 | 0.8348 |
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- | 0.579 | 2.99 | 800 | 0.5727 | 0.8260 |
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- | 0.4298 | 3.36 | 900 | 0.5906 | 0.8278 |
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- | 0.3999 | 3.73 | 1000 | 0.5693 | 0.8348 |
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- | 0.414 | 4.1 | 1100 | 0.5115 | 0.8401 |
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- | 0.408 | 4.48 | 1200 | 0.5281 | 0.8366 |
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- | 0.2794 | 4.85 | 1300 | 0.5269 | 0.8453 |
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- | 0.3881 | 5.22 | 1400 | 0.5246 | 0.8471 |
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- | 0.3097 | 5.6 | 1500 | 0.4926 | 0.8524 |
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- | 0.2272 | 5.97 | 1600 | 0.5248 | 0.8506 |
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- | 0.2796 | 6.34 | 1700 | 0.5053 | 0.8612 |
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- | 0.3279 | 6.72 | 1800 | 0.5019 | 0.8629 |
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- | 0.2674 | 7.09 | 1900 | 0.4922 | 0.8541 |
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- | 0.1587 | 7.46 | 2000 | 0.5443 | 0.8453 |
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- | 0.1969 | 7.84 | 2100 | 0.4967 | 0.8453 |
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- | 0.2137 | 8.21 | 2200 | 0.5276 | 0.8453 |
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- | 0.1523 | 8.58 | 2300 | 0.5574 | 0.8401 |
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- | 0.1046 | 8.96 | 2400 | 0.5302 | 0.8506 |
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- | 0.2494 | 9.33 | 2500 | 0.5222 | 0.8594 |
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- | 0.1924 | 9.7 | 2600 | 0.5271 | 0.8506 |
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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: 0.8347978910369068
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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: 0.7013
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+ - Accuracy: 0.8348
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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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+ | 0.255 | 0.37 | 100 | 0.7616 | 0.7926 |
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+ | 0.2048 | 0.75 | 200 | 0.7247 | 0.8084 |
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+ | 0.3763 | 1.12 | 300 | 0.6130 | 0.8330 |
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+ | 0.307 | 1.49 | 400 | 0.8137 | 0.7891 |
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+ | 0.3542 | 1.87 | 500 | 0.6612 | 0.8014 |
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+ | 0.3518 | 2.24 | 600 | 0.6965 | 0.8190 |
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+ | 0.3706 | 2.61 | 700 | 0.7254 | 0.8049 |
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+ | 0.4084 | 2.99 | 800 | 0.6746 | 0.8102 |
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+ | 0.2533 | 3.36 | 900 | 0.6867 | 0.8190 |
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+ | 0.3147 | 3.73 | 1000 | 0.7077 | 0.8190 |
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+ | 0.3182 | 4.1 | 1100 | 0.6661 | 0.8190 |
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+ | 0.2248 | 4.48 | 1200 | 0.6632 | 0.8418 |
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+ | 0.1617 | 4.85 | 1300 | 0.7277 | 0.8172 |
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+ | 0.2578 | 5.22 | 1400 | 0.7114 | 0.8190 |
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+ | 0.1864 | 5.6 | 1500 | 0.7554 | 0.8172 |
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+ | 0.3134 | 5.97 | 1600 | 0.7593 | 0.8155 |
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+ | 0.24 | 6.34 | 1700 | 0.7511 | 0.8260 |
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+ | 0.2359 | 6.72 | 1800 | 0.7502 | 0.8137 |
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+ | 0.2322 | 7.09 | 1900 | 0.6953 | 0.8348 |
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+ | 0.1514 | 7.46 | 2000 | 0.7121 | 0.8260 |
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+ | 0.2089 | 7.84 | 2100 | 0.6931 | 0.8278 |
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+ | 0.2245 | 8.21 | 2200 | 0.7087 | 0.8330 |
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+ | 0.1328 | 8.58 | 2300 | 0.7003 | 0.8313 |
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+ | 0.1304 | 8.96 | 2400 | 0.7306 | 0.8225 |
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+ | 0.1514 | 9.33 | 2500 | 0.7162 | 0.8260 |
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+ | 0.2571 | 9.7 | 2600 | 0.7013 | 0.8348 |
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  ### Framework versions
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