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Encore02
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vit-weldclassifyv4

Image Classification
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TensorBoard
Safetensors
vit
Generated from Trainer
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  1. README.md +18 -19
  2. data/events.out.tfevents.1730710942.0894b137f84e.248.0 +2 -2
  3. model.safetensors +1 -1
README.md CHANGED
@@ -3,7 +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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  - generated_from_trainer
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  datasets:
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  - imagefolder
@@ -24,7 +23,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.9172661870503597
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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
@@ -34,8 +33,8 @@ should probably proofread and complete it, then remove this comment. -->
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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: 0.2732
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- - Accuracy: 0.9173
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  ## Model description
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@@ -67,21 +66,21 @@ 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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- | 0.8791 | 0.6410 | 100 | 0.7507 | 0.7014 |
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- | 0.7436 | 1.2821 | 200 | 0.5400 | 0.7698 |
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- | 0.4783 | 1.9231 | 300 | 0.4832 | 0.8345 |
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- | 0.3055 | 2.5641 | 400 | 0.2734 | 0.9101 |
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- | 0.2407 | 3.2051 | 500 | 0.2732 | 0.9173 |
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- | 0.1367 | 3.8462 | 600 | 0.4062 | 0.8525 |
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- | 0.0943 | 4.4872 | 700 | 0.3188 | 0.9137 |
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- | 0.0938 | 5.1282 | 800 | 0.3211 | 0.9173 |
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- | 0.0352 | 5.7692 | 900 | 0.3002 | 0.9281 |
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- | 0.0054 | 6.4103 | 1000 | 0.3863 | 0.9245 |
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- | 0.0397 | 7.0513 | 1100 | 0.3790 | 0.9317 |
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- | 0.0038 | 7.6923 | 1200 | 0.2968 | 0.9388 |
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- | 0.0035 | 8.3333 | 1300 | 0.2937 | 0.9353 |
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- | 0.003 | 8.9744 | 1400 | 0.3026 | 0.9388 |
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- | 0.0031 | 9.6154 | 1500 | 0.3090 | 0.9388 |
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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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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9136690647482014
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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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  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: 0.3569
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+ - Accuracy: 0.9137
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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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+ | 0.8207 | 0.6410 | 100 | 1.0336 | 0.5647 |
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+ | 0.6506 | 1.2821 | 200 | 1.1982 | 0.5791 |
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+ | 0.5324 | 1.9231 | 300 | 0.6060 | 0.7770 |
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+ | 0.2486 | 2.5641 | 400 | 0.7294 | 0.7518 |
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+ | 0.1366 | 3.2051 | 500 | 0.4832 | 0.8417 |
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+ | 0.3124 | 3.8462 | 600 | 0.8676 | 0.7626 |
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+ | 0.0296 | 4.4872 | 700 | 0.4233 | 0.8885 |
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+ | 0.0723 | 5.1282 | 800 | 0.4470 | 0.8849 |
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+ | 0.0342 | 5.7692 | 900 | 0.3406 | 0.9173 |
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+ | 0.0055 | 6.4103 | 1000 | 0.3301 | 0.9209 |
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+ | 0.0048 | 7.0513 | 1100 | 0.3471 | 0.9173 |
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+ | 0.0036 | 7.6923 | 1200 | 0.3346 | 0.9137 |
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+ | 0.003 | 8.3333 | 1300 | 0.3498 | 0.9137 |
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+ | 0.003 | 8.9744 | 1400 | 0.3549 | 0.9101 |
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+ | 0.0027 | 9.6154 | 1500 | 0.3569 | 0.9137 |
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  ### Framework versions
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