Model save

README.md

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+---
+license: apache-2.0
+base_model: moreover18/vit-base-patch16-224-in21k-finetuned-eurosat
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: vit-base-patch16-224-in21k-finetuned-eurosat-finetuned2
+  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: 0.9251711510905907
+---
+
+<!-- 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. -->
+
+# vit-base-patch16-224-in21k-finetuned-eurosat-finetuned2
+
+This model is a fine-tuned version of [moreover18/vit-base-patch16-224-in21k-finetuned-eurosat](https://huggingface.co/moreover18/vit-base-patch16-224-in21k-finetuned-eurosat) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1871
+- Accuracy: 0.9252
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 64
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.2258        | 0.25  | 100  | 0.2074          | 0.9155   |
+| 0.2291        | 0.51  | 200  | 0.2039          | 0.9132   |
+| 0.212         | 0.76  | 300  | 0.1969          | 0.9147   |
+| 0.2126        | 1.02  | 400  | 0.2026          | 0.9163   |
+| 0.1822        | 1.27  | 500  | 0.1952          | 0.9175   |
+| 0.1716        | 1.53  | 600  | 0.1892          | 0.9225   |
+| 0.1847        | 1.78  | 700  | 0.1823          | 0.9261   |
+| 0.1693        | 2.04  | 800  | 0.1879          | 0.9239   |
+| 0.1438        | 2.29  | 900  | 0.1962          | 0.9206   |
+| 0.1431        | 2.55  | 1000 | 0.1868          | 0.9261   |
+| 0.1419        | 2.8   | 1100 | 0.1871          | 0.9252   |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 1.12.1+cu116
+- Datasets 2.4.0
+- Tokenizers 0.15.0

runs/Nov16_18-51-34_n02vrdt4ok/events.out.tfevents.1700160745.n02vrdt4ok.32.0

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