Model save

README.md

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+---
+license: apache-2.0
+base_model: facebook/convnextv2-base-22k-384
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: convnext-base
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: validation
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9439363817097416
+---
+
+<!-- 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. -->
+
+# convnext-base
+
+This model is a fine-tuned version of [facebook/convnextv2-base-22k-384](https://huggingface.co/facebook/convnextv2-base-22k-384) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2946
+- Accuracy: 0.9439
+
+## 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: 0.0001
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 0.5947        | 1.0   | 1099  | 0.4242          | 0.8684   |
+| 0.4798        | 2.0   | 2198  | 0.4242          | 0.8728   |
+| 0.3625        | 3.0   | 3297  | 0.3553          | 0.9078   |
+| 0.2777        | 4.0   | 4396  | 0.3241          | 0.9185   |
+| 0.2368        | 5.0   | 5495  | 0.3413          | 0.9245   |
+| 0.1635        | 6.0   | 6594  | 0.3116          | 0.9356   |
+| 0.1564        | 7.0   | 7693  | 0.2997          | 0.9360   |
+| 0.1082        | 8.0   | 8792  | 0.2916          | 0.9451   |
+| 0.1146        | 9.0   | 9891  | 0.2963          | 0.9431   |
+| 0.0801        | 10.0  | 10990 | 0.2946          | 0.9439   |
+
+
+### Framework versions
+
+- Transformers 4.39.3
+- Pytorch 2.1.2
+- Datasets 2.18.0
+- Tokenizers 0.15.2

model.safetensors

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