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Model save

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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
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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: Mahadih534/brain-tumor-dataset
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  type: imagefolder
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  config: default
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  split: train
@@ -31,9 +30,9 @@ should probably proofread and complete it, then remove this comment. -->
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  # vit-base-oxford-brain-tumor
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- This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the Mahadih534/brain-tumor-dataset dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6331
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  - Accuracy: 0.6154
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  ## Model description
@@ -53,25 +52,23 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 0.0003
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  - train_batch_size: 16
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  - eval_batch_size: 8
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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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- - num_epochs: 7
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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 | 13 | 0.6259 | 0.64 |
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- | No log | 2.0 | 26 | 0.5560 | 0.8 |
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- | No log | 3.0 | 39 | 0.5105 | 0.88 |
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- | No log | 4.0 | 52 | 0.4766 | 0.88 |
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- | No log | 5.0 | 65 | 0.4543 | 0.88 |
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- | No log | 6.0 | 78 | 0.4433 | 0.88 |
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- | No log | 7.0 | 91 | 0.4400 | 0.88 |
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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
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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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  # vit-base-oxford-brain-tumor
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+ This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6187
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  - Accuracy: 0.6154
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  ## Model description
 
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 0.0002
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  - train_batch_size: 16
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  - eval_batch_size: 8
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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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+ - num_epochs: 5
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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 | 13 | 0.5587 | 0.68 |
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+ | No log | 2.0 | 26 | 0.5209 | 0.8 |
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+ | No log | 3.0 | 39 | 0.4983 | 0.84 |
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+ | No log | 4.0 | 52 | 0.4822 | 0.8 |
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+ | No log | 5.0 | 65 | 0.4770 | 0.8 |
 
 
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  ### Framework versions
runs/Jun09_18-01-02_3461f2516c4a/events.out.tfevents.1717957052.3461f2516c4a.3087.9 ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:74f1eab7c6157b6ffd87074216a78a03216e664c9581373dd08a32f8afcf2f8c
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+ size 405