Model save

README.md

@@ -4,7 +4,7 @@ base_model: microsoft/swinv2-tiny-patch4-window8-256
 tags:
 - generated_from_trainer
 datasets:
-- image_folder
+- imagefolder
 metrics:
 - accuracy
 model-index:
@@ -14,15 +14,15 @@ model-index:
       name: Image Classification
       type: image-classification
     dataset:
-      name: image_folder
-      type: image_folder
+      name: imagefolder
+      type: imagefolder
       config: default
-      split: train
+      split: validation
       args: default
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9615316328342309
+      value: 0.983
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -30,10 +30,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # swinv2-tiny-patch4-window8-256-finetuned-eurosat
 
-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 image_folder dataset.
+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.
 It achieves the following results on the evaluation set:
-- Loss: 0.1067
-- Accuracy: 0.9615
+- Loss: 0.0482
+- Accuracy: 0.983
 
 ## Model description
 
@@ -53,28 +53,35 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 5e-05
-- train_batch_size: 32
-- eval_batch_size: 32
+- train_batch_size: 450
+- eval_batch_size: 450
 - seed: 42
 - gradient_accumulation_steps: 4
-- total_train_batch_size: 128
+- total_train_batch_size: 1800
 - 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
+- num_epochs: 10
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.2183        | 1.0   | 1188 | 0.1283          | 0.9542   |
-| 0.2099        | 2.0   | 2376 | 0.1188          | 0.9570   |
-| 0.1668        | 3.0   | 3564 | 0.1067          | 0.9615   |
+| 0.3991        | 1.0   | 46   | 0.2074          | 0.933    |
+| 0.1629        | 2.0   | 92   | 0.0946          | 0.971    |
+| 0.1294        | 3.0   | 138  | 0.0692          | 0.977    |
+| 0.1164        | 4.0   | 184  | 0.0572          | 0.982    |
+| 0.1028        | 5.0   | 230  | 0.0494          | 0.984    |
+| 0.0893        | 6.0   | 276  | 0.0487          | 0.982    |
+| 0.0843        | 7.0   | 322  | 0.0472          | 0.984    |
+| 0.0805        | 8.0   | 368  | 0.0437          | 0.983    |
+| 0.0705        | 9.0   | 414  | 0.0523          | 0.982    |
+| 0.0712        | 10.0  | 460  | 0.0482          | 0.983    |
 
 
 ### Framework versions
 
-- Transformers 4.33.0
-- Pytorch 2.0.0
-- Datasets 2.1.0
-- Tokenizers 0.13.3
+- Transformers 4.35.0
+- Pytorch 2.1.0+cu121
+- Datasets 2.14.6
+- Tokenizers 0.14.1

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:726a1ce1d5f472fc494c05668bda4894b402ac4514a25ca6bfab437fb718957a
+oid sha256:e02b84225255abc6c662527c89669ed7cbd1fdb723437f34ead9c17328fa9f17
 size 110356296