Model save
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- pytorch_model.bin +1 -1
- training_args.bin +1 -1
README.md
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---
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base_model: /content/drive/MyDrive/Seizure_EEG_Research/ViT_Seizure_Detection
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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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- arrow
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model-index:
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- name: ViT_Seizure_Detection
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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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# ViT_Seizure_Detection
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This model
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It achieves the following results on the evaluation set:
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- eval_runtime: 1091.8559
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- eval_samples_per_second: 104.441
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- eval_steps_per_second: 13.056
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- epoch: 3.14
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- step: 40000
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## Model description
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- lr_scheduler_type: linear
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- num_epochs: 4
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### Framework versions
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- Transformers 4.34.1
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---
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tags:
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- generated_from_trainer
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datasets:
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- arrow
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metrics:
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- matthews_correlation
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model-index:
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- name: ViT_Seizure_Detection
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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: arrow
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type: arrow
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config: default
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split: test
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args: default
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metrics:
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- name: Matthews Correlation
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type: matthews_correlation
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value: 0.4389188148304588
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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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# ViT_Seizure_Detection
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This model was trained from scratch on the arrow dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3495
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- Matthews Correlation: 0.4389
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## Model description
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- lr_scheduler_type: linear
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- num_epochs: 4
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
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|:-------------:|:-----:|:-----:|:---------------:|:--------------------:|
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| 0.0742 | 0.79 | 10000 | 0.2080 | 0.4431 |
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| 0.0409 | 1.57 | 20000 | 0.2175 | 0.4470 |
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| 0.0345 | 2.36 | 30000 | 0.2514 | 0.4717 |
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| 0.0184 | 3.14 | 40000 | 0.3040 | 0.4261 |
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| 0.0092 | 3.93 | 50000 | 0.3495 | 0.4389 |
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### Framework versions
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- Transformers 4.34.1
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pytorch_model.bin
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training_args.bin
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