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---
library_name: transformers
license: other
base_model: nancyalarabawy/segformer-finetuned-segments-plantleafdisease-may-25
tags:
- vision
- image-segmentation
- generated_from_trainer
model-index:
- name: segformer-finetuned-segments-plantleafdisease-DEC
results: []
---
<!-- 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. -->
# segformer-finetuned-segments-plantleafdisease-DEC
This model is a fine-tuned version of [nancyalarabawy/segformer-finetuned-segments-plantleafdisease-may-25](https://huggingface.co/nancyalarabawy/segformer-finetuned-segments-plantleafdisease-may-25) on the all plus aug dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.0249
- eval_mean_iou: 0.7357
- eval_mean_accuracy: 0.9156
- eval_overall_accuracy: 0.9916
- eval_accuracy_unlabeled: nan
- eval_accuracy_healthy: 0.9794
- eval_accuracy_blast: 0.8521
- eval_accuracy_background: 0.9975
- eval_accuracy_alstonia herpes: 0.8728
- eval_accuracy_mango anthracnose: 0.9309
- eval_accuracy_pomengrate spots: 0.9346
- eval_accuracy_blight spots: 0.8934
- eval_accuracy_chlorisis: 0.9443
- eval_accuracy_leaf spots: 0.9201
- eval_accuracy_apple scab: 0.8382
- eval_accuracy_black rot: 0.8716
- eval_accuracy_cedar rust: 0.9525
- eval_iou_unlabeled: 0.0
- eval_iou_healthy: 0.9690
- eval_iou_blast: 0.7758
- eval_iou_background: 0.9954
- eval_iou_alstonia herpes: 0.7583
- eval_iou_mango anthracnose: 0.6425
- eval_iou_pomengrate spots: 0.8681
- eval_iou_blight spots: 0.6074
- eval_iou_chlorisis: 0.9190
- eval_iou_leaf spots: 0.7070
- eval_iou_apple scab: 0.7455
- eval_iou_black rot: 0.8060
- eval_iou_cedar rust: 0.7695
- eval_runtime: 155.0063
- eval_samples_per_second: 16.915
- eval_steps_per_second: 1.058
- epoch: 13.3486
- step: 17500
## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 200
- num_epochs: 15
### Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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