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zqTensor
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vit-base-beans

Image Classification
Transformers
Safetensors
vit
vision
Generated from Trainer
Inference Endpoints
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  1. README.md +44 -6
  2. model.safetensors +1 -1
README.md CHANGED
@@ -3,8 +3,6 @@ library_name: transformers
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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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- - vision
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  - generated_from_trainer
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  metrics:
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  - accuracy
@@ -18,10 +16,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # vit-base-beans
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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 beans dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0656
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- - Accuracy: 0.9925
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  ## Model description
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@@ -50,7 +48,7 @@ The following hyperparameters were used during training:
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  - total_eval_batch_size: 16
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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: 5.0
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  ### Training results
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@@ -61,6 +59,46 @@ The following hyperparameters were used during training:
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  | 0.1438 | 3.0 | 390 | 0.9699 | 0.0981 |
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  | 0.0833 | 4.0 | 520 | 0.9925 | 0.0656 |
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  | 0.1107 | 5.0 | 650 | 0.9774 | 0.0817 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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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  metrics:
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  - accuracy
 
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  # vit-base-beans
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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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0079
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+ - Accuracy: 1.0
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  ## Model description
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  - total_eval_batch_size: 16
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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: 50.0
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  ### Training results
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  | 0.1438 | 3.0 | 390 | 0.9699 | 0.0981 |
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  | 0.0833 | 4.0 | 520 | 0.9925 | 0.0656 |
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  | 0.1107 | 5.0 | 650 | 0.9774 | 0.0817 |
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+ | 0.098 | 11.0 | 715 | 0.0570 | 0.9925 |
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+ | 0.0935 | 12.0 | 780 | 0.0418 | 1.0 |
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+ | 0.0907 | 13.0 | 845 | 0.1093 | 0.9699 |
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+ | 0.0947 | 14.0 | 910 | 0.0347 | 1.0 |
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+ | 0.1259 | 15.0 | 975 | 0.0710 | 0.9850 |
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+ | 0.0325 | 16.0 | 1040 | 0.0587 | 0.9774 |
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+ | 0.1397 | 17.0 | 1105 | 0.0495 | 0.9925 |
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+ | 0.0456 | 18.0 | 1170 | 0.0519 | 0.9774 |
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+ | 0.0439 | 19.0 | 1235 | 0.0216 | 1.0 |
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+ | 0.0484 | 20.0 | 1300 | 0.0316 | 0.9925 |
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+ | 0.0276 | 21.0 | 1365 | 0.0192 | 1.0 |
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+ | 0.0348 | 22.0 | 1430 | 0.0177 | 1.0 |
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+ | 0.0326 | 23.0 | 1495 | 0.0175 | 1.0 |
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+ | 0.1014 | 24.0 | 1560 | 0.0235 | 0.9925 |
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+ | 0.0395 | 25.0 | 1625 | 0.0451 | 0.9850 |
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+ | 0.0265 | 26.0 | 1690 | 0.0297 | 0.9925 |
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+ | 0.0569 | 27.0 | 1755 | 0.0263 | 0.9925 |
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+ | 0.0666 | 28.0 | 1820 | 0.0245 | 0.9850 |
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+ | 0.0285 | 29.0 | 1885 | 0.0418 | 0.9774 |
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+ | 0.0892 | 30.0 | 1950 | 0.0204 | 0.9925 |
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+ | 0.0371 | 31.0 | 2015 | 0.0339 | 0.9850 |
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+ | 0.0105 | 32.0 | 2080 | 0.0143 | 1.0 |
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+ | 0.0563 | 33.0 | 2145 | 0.0140 | 1.0 |
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+ | 0.0573 | 34.0 | 2210 | 0.0102 | 1.0 |
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+ | 0.0409 | 35.0 | 2275 | 0.0096 | 1.0 |
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+ | 0.0523 | 36.0 | 2340 | 0.0149 | 0.9925 |
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+ | 0.0131 | 37.0 | 2405 | 0.0197 | 0.9925 |
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+ | 0.0329 | 38.0 | 2470 | 0.0109 | 1.0 |
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+ | 0.0577 | 39.0 | 2535 | 0.0096 | 1.0 |
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+ | 0.0085 | 40.0 | 2600 | 0.0147 | 0.9925 |
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+ | 0.0618 | 41.0 | 2665 | 0.0094 | 1.0 |
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+ | 0.0847 | 42.0 | 2730 | 0.0197 | 0.9925 |
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+ | 0.0291 | 43.0 | 2795 | 0.0089 | 1.0 |
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+ | 0.0568 | 44.0 | 2860 | 0.0087 | 1.0 |
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+ | 0.0077 | 45.0 | 2925 | 0.0104 | 1.0 |
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+ | 0.008 | 46.0 | 2990 | 0.0138 | 1.0 |
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+ | 0.0272 | 47.0 | 3055 | 0.0081 | 1.0 |
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+ | 0.008 | 48.0 | 3120 | 0.0084 | 1.0 |
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+ | 0.0112 | 49.0 | 3185 | 0.0082 | 1.0 |
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+ | 0.013 | 50.0 | 3250 | 0.0079 | 1.0 |
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  ### Framework versions
model.safetensors CHANGED
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