Model save

README.md

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+---
+license: apache-2.0
+base_model: facebook/convnextv2-base-22k-224
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: convnextv2-base-22k-224-finetuned-cassava-leaf-disease
+  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: 0.8827102803738318
+---
+
+<!-- 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. -->
+
+# convnextv2-base-22k-224-finetuned-cassava-leaf-disease
+
+This model is a fine-tuned version of [facebook/convnextv2-base-22k-224](https://huggingface.co/facebook/convnextv2-base-22k-224) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3524
+- Accuracy: 0.8827
+
+## 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: 360
+- eval_batch_size: 360
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 1440
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 16
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.504         | 0.96  | 13   | 0.9739          | 0.6159   |
+| 0.9073        | 2.0   | 27   | 0.5204          | 0.8187   |
+| 0.4289        | 2.96  | 40   | 0.4312          | 0.85     |
+| 0.3901        | 4.0   | 54   | 0.3916          | 0.8645   |
+| 0.34          | 4.96  | 67   | 0.3755          | 0.8715   |
+| 0.3326        | 6.0   | 81   | 0.3746          | 0.8710   |
+| 0.3153        | 6.96  | 94   | 0.3684          | 0.8771   |
+| 0.3103        | 8.0   | 108  | 0.3543          | 0.8780   |
+| 0.292         | 8.96  | 121  | 0.3620          | 0.8804   |
+| 0.2953        | 10.0  | 135  | 0.3545          | 0.8794   |
+| 0.2879        | 10.96 | 148  | 0.3550          | 0.8808   |
+| 0.2779        | 12.0  | 162  | 0.3504          | 0.8799   |
+| 0.2736        | 12.96 | 175  | 0.3554          | 0.8818   |
+| 0.2769        | 14.0  | 189  | 0.3526          | 0.8846   |
+| 0.2625        | 14.96 | 202  | 0.3527          | 0.8813   |
+| 0.2625        | 15.41 | 208  | 0.3524          | 0.8827   |
+
+
+### Framework versions
+
+- Transformers 4.39.3
+- Pytorch 2.2.1
+- Datasets 2.18.0
+- Tokenizers 0.15.1

model.safetensors

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