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Safawat
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finetuned-electrical-images

Image Classification
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vit
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  1. README.md +24 -25
  2. model.safetensors +1 -1
  3. runs/Apr26_13-59-20_cee49ebfb78a/events.out.tfevents.1714139986.cee49ebfb78a.754.0 +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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  metrics:
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  - accuracy
@@ -16,10 +15,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # finetuned-electrical-images
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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 Electrical_components(VIT) dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3634
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- - Accuracy: 0.8977
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  ## Model description
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@@ -50,27 +49,27 @@ 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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- | 0.7236 | 0.4651 | 100 | 0.6396 | 0.8102 |
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- | 0.7243 | 0.9302 | 200 | 0.5124 | 0.8333 |
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- | 0.4288 | 1.3953 | 300 | 0.4514 | 0.8630 |
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- | 0.5744 | 1.8605 | 400 | 0.6154 | 0.8102 |
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- | 0.4077 | 2.3256 | 500 | 0.4612 | 0.8614 |
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- | 0.496 | 2.7907 | 600 | 0.4359 | 0.8729 |
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- | 0.3446 | 3.2558 | 700 | 0.4276 | 0.8696 |
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- | 0.3347 | 3.7209 | 800 | 0.4259 | 0.8795 |
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- | 0.3868 | 4.1860 | 900 | 0.4642 | 0.8548 |
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- | 0.36 | 4.6512 | 1000 | 0.4242 | 0.8696 |
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- | 0.295 | 5.1163 | 1100 | 0.4204 | 0.8812 |
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- | 0.2342 | 5.5814 | 1200 | 0.3933 | 0.8911 |
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- | 0.1629 | 6.0465 | 1300 | 0.3634 | 0.8977 |
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- | 0.2041 | 6.5116 | 1400 | 0.4007 | 0.8911 |
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- | 0.1668 | 6.9767 | 1500 | 0.3843 | 0.8927 |
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- | 0.0976 | 7.4419 | 1600 | 0.4062 | 0.8927 |
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- | 0.1275 | 7.9070 | 1700 | 0.3861 | 0.8894 |
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- | 0.1063 | 8.3721 | 1800 | 0.4011 | 0.8911 |
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- | 0.1658 | 8.8372 | 1900 | 0.3840 | 0.9043 |
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- | 0.1 | 9.3023 | 2000 | 0.3873 | 0.9010 |
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- | 0.1045 | 9.7674 | 2100 | 0.3787 | 0.9076 |
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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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  # finetuned-electrical-images
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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: 0.4092
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+ - Accuracy: 0.8927
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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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+ | 0.7116 | 0.4651 | 100 | 0.6399 | 0.7921 |
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+ | 0.6953 | 0.9302 | 200 | 0.5589 | 0.8086 |
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+ | 0.4078 | 1.3953 | 300 | 0.4946 | 0.8399 |
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+ | 0.5852 | 1.8605 | 400 | 0.4872 | 0.8399 |
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+ | 0.4993 | 2.3256 | 500 | 0.4687 | 0.8597 |
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+ | 0.4479 | 2.7907 | 600 | 0.3986 | 0.8845 |
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+ | 0.4101 | 3.2558 | 700 | 0.4385 | 0.8729 |
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+ | 0.283 | 3.7209 | 800 | 0.4413 | 0.8762 |
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+ | 0.3959 | 4.1860 | 900 | 0.4121 | 0.8729 |
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+ | 0.318 | 4.6512 | 1000 | 0.4397 | 0.8696 |
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+ | 0.2401 | 5.1163 | 1100 | 0.4887 | 0.8680 |
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+ | 0.1273 | 5.5814 | 1200 | 0.4224 | 0.8663 |
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+ | 0.1101 | 6.0465 | 1300 | 0.4378 | 0.8779 |
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+ | 0.1773 | 6.5116 | 1400 | 0.3730 | 0.8845 |
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+ | 0.2248 | 6.9767 | 1500 | 0.3726 | 0.8861 |
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+ | 0.0987 | 7.4419 | 1600 | 0.4398 | 0.8845 |
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+ | 0.16 | 7.9070 | 1700 | 0.4171 | 0.8828 |
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+ | 0.1224 | 8.3721 | 1800 | 0.4336 | 0.8878 |
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+ | 0.2111 | 8.8372 | 1900 | 0.3948 | 0.8944 |
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+ | 0.112 | 9.3023 | 2000 | 0.4004 | 0.8944 |
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+ | 0.0962 | 9.7674 | 2100 | 0.4092 | 0.8927 |
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  ### Framework versions
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