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ef53e6b
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e1de35d
End of training
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README.md
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---
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license: apache-2.0
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base_model: microsoft/swinv2-tiny-patch4-window8-256
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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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- recall
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- f1
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- precision
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model-index:
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- name: swinv2-tiny-patch4-window8-256-finetuned-ind-17-imbalanced-aadhaarmask
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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: 0.842911877394636
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- name: Recall
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type: recall
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value: 0.842911877394636
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- name: F1
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type: f1
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value: 0.8385784325520474
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- name: Precision
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type: precision
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value: 0.8458268067820361
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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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# swinv2-tiny-patch4-window8-256-finetuned-ind-17-imbalanced-aadhaarmask
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This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4148
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- Accuracy: 0.8429
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- Recall: 0.8429
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- F1: 0.8386
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- Precision: 0.8458
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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: 5e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 32
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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 | Recall | F1 | Precision |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
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| 0.6967 | 0.9974 | 293 | 0.6602 | 0.7854 | 0.7854 | 0.7724 | 0.7895 |
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| 0.5364 | 1.9983 | 587 | 0.4842 | 0.8221 | 0.8221 | 0.8126 | 0.8248 |
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| 0.4465 | 2.9991 | 881 | 0.4177 | 0.8323 | 0.8323 | 0.8292 | 0.8317 |
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| 0.4608 | 4.0 | 1175 | 0.4302 | 0.8340 | 0.8340 | 0.8285 | 0.8428 |
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| 0.4887 | 4.9974 | 1468 | 0.3843 | 0.8421 | 0.8421 | 0.8385 | 0.8487 |
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| 0.3815 | 5.9983 | 1762 | 0.4016 | 0.8438 | 0.8438 | 0.8398 | 0.8460 |
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| 0.2856 | 6.9991 | 2056 | 0.3771 | 0.8506 | 0.8506 | 0.8464 | 0.8506 |
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| 0.4721 | 8.0 | 2350 | 0.3709 | 0.8391 | 0.8391 | 0.8382 | 0.8417 |
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| 0.3126 | 8.9974 | 2643 | 0.3668 | 0.8348 | 0.8348 | 0.8330 | 0.8352 |
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| 0.3791 | 9.9745 | 2930 | 0.3643 | 0.8335 | 0.8335 | 0.8322 | 0.8340 |
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### Framework versions
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- Transformers 4.40.1
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- Pytorch 2.2.0a0+81ea7a4
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- Datasets 2.19.0
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- Tokenizers 0.19.1
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emissions.csv
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timestamp,project_name,run_id,duration,emissions,emissions_rate,cpu_power,gpu_power,ram_power,cpu_energy,gpu_energy,ram_energy,energy_consumed,country_name,country_iso_code,region,cloud_provider,cloud_region,os,python_version,codecarbon_version,cpu_count,cpu_model,gpu_count,gpu_model,longitude,latitude,ram_total_size,tracking_mode,on_cloud,pue
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2024-05-01T12:39:05,codecarbon,9ab4814f-b2cf-4121-89db-25302f8f25f3,1153.797636270523,0.0001095405967162954,9.493917587694916e-08,42.5,68.2087103743631,11.667008399963379,0.013620646490487786,0.028721619366166018,0.0037370449309994083,0.04607931078765321,Canada,CAN,quebec,,,Linux-5.15.0-105-generic-x86_64-with-glibc2.35,3.10.12,2.3.5,32,13th Gen Intel(R) Core(TM) i9-13900K,1,1 x NVIDIA GeForce RTX 4060 Ti,-71.2,46.8,31.112022399902344,machine,N,1.0
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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runs/May01_12-19-50_60f4804cf903/events.out.tfevents.1714567177.60f4804cf903.2170.1
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version https://git-lfs.github.com/spec/v1
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size 560
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