Create README.md

README.md

@@ -1,80 +1,9 @@
 ---
-license: apache-2.0
-base_model: microsoft/swin-tiny-patch4-window7-224
-tags:
-- generated_from_trainer
 datasets:
-- imagefolder
-metrics:
-- accuracy
-model-index:
-- name: swin-tiny-patch4-window7-224-finetuned-eurosat
-  results:
-  - task:
-      name: Image Classification
-      type: image-classification
-    dataset:
-      name: imagefolder
-      type: imagefolder
-      config: default
-      split: train
-      args: default
-    metrics:
-    - name: Accuracy
-      type: accuracy
-      value: 0.9884393063583815
----
-
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
-
-# swin-tiny-patch4-window7-224-finetuned-eurosat
-
-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.
-It achieves the following results on the evaluation set:
-- Loss: 0.0338
-- Accuracy: 0.9884
-
-## Model description
-
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
-
-## Training procedure
-
-### Training hyperparameters
-
-The following hyperparameters were used during training:
-- learning_rate: 5e-05
-- train_batch_size: 32
-- eval_batch_size: 32
-- seed: 42
-- gradient_accumulation_steps: 4
-- total_train_batch_size: 128
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
-- lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 3
-
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.4088        | 0.98  | 12   | 0.0338          | 0.9884   |
-| 0.0542        | 1.96  | 24   | 0.0241          | 0.9884   |
-| 0.0327        | 2.94  | 36   | 0.0156          | 0.9884   |
-
-
-### Framework versions
-
-- Transformers 4.33.3
-- Pytorch 2.0.1+cu118
-- Datasets 2.14.5
-- Tokenizers 0.13.3
+- DamarJati/NSFW-filter-DecentScan
+language:
+- en
+pipeline_tag: image-classification
+tags:
+- art
+---