Model save

README.md

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+---
+license: apache-2.0
+base_model: facebook/convnextv2-base-1k-224
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: convnextv2-base-1k-224-finetuned-cassava-leaf-disease-randomflip
+  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: 0.8766355140186916
+---
+
+<!-- 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-1k-224-finetuned-cassava-leaf-disease-randomflip
+
+This model is a fine-tuned version of [facebook/convnextv2-base-1k-224](https://huggingface.co/facebook/convnextv2-base-1k-224) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3704
+- Accuracy: 0.8766
+
+## 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: 400
+- eval_batch_size: 400
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 1600
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.5605        | 0.98  | 12   | 1.2754          | 0.6150   |
+| 1.2015        | 1.96  | 24   | 0.9009          | 0.6290   |
+| 0.9048        | 2.94  | 36   | 0.6987          | 0.7701   |
+| 0.7362        | 4.0   | 49   | 0.5497          | 0.8206   |
+| 0.5294        | 4.98  | 61   | 0.4712          | 0.8542   |
+| 0.4777        | 5.96  | 73   | 0.4451          | 0.8547   |
+| 0.458         | 6.94  | 85   | 0.4197          | 0.8579   |
+| 0.4208        | 8.0   | 98   | 0.4084          | 0.8682   |
+| 0.4042        | 8.98  | 110  | 0.3930          | 0.8692   |
+| 0.4071        | 9.96  | 122  | 0.3879          | 0.8743   |
+| 0.3868        | 10.94 | 134  | 0.3923          | 0.8715   |
+| 0.3849        | 12.0  | 147  | 0.3763          | 0.8748   |
+| 0.3744        | 12.98 | 159  | 0.3732          | 0.8776   |
+| 0.3739        | 13.96 | 171  | 0.3708          | 0.8748   |
+| 0.361         | 14.94 | 183  | 0.3693          | 0.8818   |
+| 0.3725        | 15.67 | 192  | 0.3704          | 0.8766   |
+
+
+### Framework versions
+
+- Transformers 4.39.3
+- Pytorch 2.2.1
+- Datasets 2.18.0
+- Tokenizers 0.15.1

model.safetensors

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