jayanthspratap
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README.md
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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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- imagefolder
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metrics:
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- accuracy
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model-index:
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- name: 2024_08_15_swinv2-base-patch4-window8-256
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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: 0.8181818181818182
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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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should probably proofread and complete it, then remove this comment. -->
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# 2024_08_15_swinv2-base-patch4-window8-256
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This model was trained from scratch on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4972
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- Accuracy: 0.8182
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 1e-05
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- train_batch_size: 1
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- eval_batch_size: 1
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 4
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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: 2
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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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| 0.4908 | 1.0 | 87 | 0.4882 | 0.7955 |
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| 1.0014 | 2.0 | 174 | 0.4972 | 0.8182 |
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### Framework versions
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- Transformers 4.42.3
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- Pytorch 2.3.1+cu118
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- Datasets 2.20.0
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- Tokenizers 0.19.1
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runs/Aug16_02-16-57_EMIMDGXA100GPU1/events.out.tfevents.1723789020.EMIMDGXA100GPU1.364265.0
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