surajjoshi
commited on
Commit
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Parent(s):
ccaa639
Model save
Browse files- .DS_Store +2 -2
- README.md +47 -2
- all_results.json +8 -8
- eval_results.json +9 -8
.DS_Store
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version https://git-lfs.github.com/spec/v1
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size
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version https://git-lfs.github.com/spec/v1
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size 10244
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README.md
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license: apache-2.0
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tags:
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- generated_from_trainer
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model-index:
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- name: swin-tiny-patch4-window7-224-finetuned-brainTumorData
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results:
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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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# swin-tiny-patch4-window7-224-finetuned-brainTumorData
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This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on
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## Model description
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 4
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### Framework versions
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- Transformers 4.23.1
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license: apache-2.0
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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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- accuracy
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- f1
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- recall
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- precision
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model-index:
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- name: swin-tiny-patch4-window7-224-finetuned-brainTumorData
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results:
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- task:
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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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args: default
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.9977843426883308
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- name: F1
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type: f1
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value: 0.9984067976633033
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- name: Recall
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type: recall
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value: 0.9978768577494692
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- name: Precision
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type: precision
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value: 0.9989373007438895
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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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# swin-tiny-patch4-window7-224-finetuned-brainTumorData
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This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0101
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- Accuracy: 0.9978
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- F1: 0.9984
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- Recall: 0.9979
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- Precision: 0.9989
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## Model description
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 4
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
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| 0.1884 | 1.0 | 95 | 0.0706 | 0.9705 | 0.9787 | 0.9756 | 0.9818 |
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| 0.1134 | 2.0 | 190 | 0.0364 | 0.9889 | 0.9920 | 0.9883 | 0.9957 |
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| 0.1031 | 3.0 | 285 | 0.0116 | 0.9963 | 0.9973 | 0.9947 | 1.0 |
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| 0.0746 | 4.0 | 380 | 0.0101 | 0.9978 | 0.9984 | 0.9979 | 0.9989 |
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### Framework versions
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- Transformers 4.23.1
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all_results.json
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{
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"epoch": 4.0,
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"eval_accuracy": 0.
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"eval_f1": 0.
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"eval_loss": 0.
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"eval_precision": 0.
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"eval_recall": 0.
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"eval_runtime":
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"eval_samples_per_second":
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"eval_steps_per_second": 0.
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"total_flos": 3.037401854071603e+17,
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"train_loss": 0.2525144927203655,
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"train_runtime": 9271.044,
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{
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"epoch": 4.0,
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"eval_accuracy": 0.9977843426883308,
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"eval_f1": 0.9984067976633033,
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"eval_loss": 0.010051622986793518,
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"eval_precision": 0.9989373007438895,
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"eval_recall": 0.9978768577494692,
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"eval_runtime": 66.6969,
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"eval_samples_per_second": 20.301,
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"eval_steps_per_second": 0.645,
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"total_flos": 3.037401854071603e+17,
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"train_loss": 0.2525144927203655,
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"train_runtime": 9271.044,
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eval_results.json
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}
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{
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"epoch": 4.0,
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"eval_accuracy": 0.9977843426883308,
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"eval_f1": 0.9984067976633033,
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"eval_loss": 0.010051622986793518,
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"eval_precision": 0.9989373007438895,
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"eval_recall": 0.9978768577494692,
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"eval_runtime": 66.6969,
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"eval_samples_per_second": 20.301,
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"eval_steps_per_second": 0.645
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}
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