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louislu9911
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convnextv2-base-1k-224-finetuned-cassava-leaf-disease

Image Classification
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convnextv2
Generated from Trainer
Eval Results
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  1. README.md +22 -22
  2. model.safetensors +1 -1
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.8570093457943925
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
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  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.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4115
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- - Accuracy: 0.8570
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  ## Model description
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@@ -53,11 +53,11 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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- - train_batch_size: 360
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- - eval_batch_size: 360
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  - seed: 42
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  - gradient_accumulation_steps: 4
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- - total_train_batch_size: 1440
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_ratio: 0.1
@@ -67,22 +67,22 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 1.5325 | 0.96 | 13 | 1.2157 | 0.6150 |
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- | 1.1879 | 2.0 | 27 | 0.8790 | 0.6678 |
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- | 0.7847 | 2.96 | 40 | 0.7251 | 0.7411 |
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- | 0.6796 | 4.0 | 54 | 0.6467 | 0.7776 |
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- | 0.5953 | 4.96 | 67 | 0.5780 | 0.8005 |
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- | 0.5199 | 6.0 | 81 | 0.5108 | 0.8234 |
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- | 0.4731 | 6.96 | 94 | 0.4794 | 0.8336 |
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- | 0.45 | 8.0 | 108 | 0.4631 | 0.8425 |
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- | 0.417 | 8.96 | 121 | 0.4448 | 0.8435 |
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- | 0.4142 | 10.0 | 135 | 0.4332 | 0.8514 |
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- | 0.3911 | 10.96 | 148 | 0.4244 | 0.8537 |
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- | 0.3764 | 12.0 | 162 | 0.4216 | 0.8537 |
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- | 0.3748 | 12.96 | 175 | 0.4152 | 0.8551 |
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- | 0.385 | 14.0 | 189 | 0.4109 | 0.8575 |
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- | 0.3615 | 14.96 | 202 | 0.4121 | 0.8570 |
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- | 0.3615 | 15.41 | 208 | 0.4115 | 0.8570 |
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  ### Framework versions
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.866822429906542
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  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.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3847
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+ - Accuracy: 0.8668
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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+ - train_batch_size: 300
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+ - eval_batch_size: 300
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  - seed: 42
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  - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 1200
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_ratio: 0.1
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 1.4746 | 0.98 | 16 | 1.1574 | 0.6150 |
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+ | 0.9672 | 1.97 | 32 | 0.8080 | 0.7084 |
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+ | 0.7544 | 2.95 | 48 | 0.6316 | 0.7832 |
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+ | 0.5568 | 4.0 | 65 | 0.5164 | 0.8350 |
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+ | 0.4714 | 4.98 | 81 | 0.4622 | 0.8486 |
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+ | 0.4361 | 5.97 | 97 | 0.4373 | 0.8509 |
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+ | 0.412 | 6.95 | 113 | 0.4347 | 0.8570 |
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+ | 0.3786 | 8.0 | 130 | 0.4091 | 0.8598 |
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+ | 0.3741 | 8.98 | 146 | 0.4161 | 0.8598 |
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+ | 0.3649 | 9.97 | 162 | 0.4062 | 0.8668 |
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+ | 0.3532 | 10.95 | 178 | 0.3931 | 0.8668 |
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+ | 0.3467 | 12.0 | 195 | 0.3884 | 0.8645 |
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+ | 0.3379 | 12.98 | 211 | 0.3850 | 0.8645 |
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+ | 0.3428 | 13.97 | 227 | 0.3911 | 0.8715 |
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+ | 0.3409 | 14.95 | 243 | 0.3887 | 0.8687 |
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+ | 0.3397 | 15.75 | 256 | 0.3847 | 0.8668 |
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  ### Framework versions
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