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tvganesh
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identify_stroke

Image Classification
Transformers
PyTorch
vit
Generated from Trainer
Eval Results (legacy)
Model card Files
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Community
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tvganesh commited on
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End of training

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  1. README.md +23 -13
README.md CHANGED
@@ -32,7 +32,7 @@ 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: 0.1320
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  - Accuracy: 1.0
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  ## Model description
@@ -53,28 +53,38 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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- - train_batch_size: 6
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  - eval_batch_size: 6
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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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  - lr_scheduler_warmup_ratio: 0.1
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- - num_epochs: 10
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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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- | No log | 1.0 | 3 | 0.2907 | 1.0 |
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- | No log | 2.0 | 6 | 0.3263 | 0.75 |
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- | No log | 3.0 | 9 | 0.1912 | 1.0 |
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- | No log | 4.0 | 12 | 0.1993 | 1.0 |
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- | No log | 5.0 | 15 | 0.1437 | 1.0 |
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- | No log | 6.0 | 18 | 0.1236 | 1.0 |
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- | 0.175 | 7.0 | 21 | 0.1102 | 1.0 |
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- | 0.175 | 8.0 | 24 | 0.0924 | 1.0 |
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- | 0.175 | 9.0 | 27 | 0.1220 | 1.0 |
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- | 0.175 | 10.0 | 30 | 0.1320 | 1.0 |
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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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: 0.0923
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  - Accuracy: 1.0
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  ## Model description
 
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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+ - train_batch_size: 8
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  - eval_batch_size: 6
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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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  - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 20
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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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+ | No log | 1.0 | 3 | 0.2842 | 1.0 |
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+ | No log | 2.0 | 6 | 0.3240 | 1.0 |
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+ | No log | 3.0 | 9 | 0.3020 | 1.0 |
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+ | No log | 4.0 | 12 | 0.2311 | 1.0 |
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+ | No log | 5.0 | 15 | 0.1781 | 1.0 |
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+ | No log | 6.0 | 18 | 0.1666 | 1.0 |
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+ | 0.2203 | 7.0 | 21 | 0.1445 | 1.0 |
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+ | 0.2203 | 8.0 | 24 | 0.1213 | 1.0 |
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+ | 0.2203 | 9.0 | 27 | 0.1166 | 1.0 |
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+ | 0.2203 | 10.0 | 30 | 0.1059 | 1.0 |
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+ | 0.2203 | 11.0 | 33 | 0.1633 | 1.0 |
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+ | 0.2203 | 12.0 | 36 | 0.1574 | 1.0 |
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+ | 0.2203 | 13.0 | 39 | 0.1010 | 1.0 |
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+ | 0.1398 | 14.0 | 42 | 0.1019 | 1.0 |
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+ | 0.1398 | 15.0 | 45 | 0.0778 | 1.0 |
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+ | 0.1398 | 16.0 | 48 | 0.0812 | 1.0 |
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+ | 0.1398 | 17.0 | 51 | 0.1087 | 1.0 |
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+ | 0.1398 | 18.0 | 54 | 0.0783 | 1.0 |
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+ | 0.1398 | 19.0 | 57 | 0.0769 | 1.0 |
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+ | 0.0992 | 20.0 | 60 | 0.0923 | 1.0 |
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  ### Framework versions