metadata
license: apache-2.0
base_model: microsoft/resnet-50
tags:
- generated_from_trainer
datasets:
- A2H0H0R1/plant-disease
metrics:
- accuracy
model-index:
- name: resnet-50-plant-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: 0.9285917496443812
resnet-50-plant-disease
This model is a fine-tuned version of microsoft/resnet-50 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.3609
- Accuracy: 0.9286
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: 100
- eval_batch_size: 100
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 400
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 3.4023 | 1.0 | 158 | 3.2949 | 0.4071 |
| 1.9184 | 2.0 | 316 | 1.5580 | 0.7788 |
| 0.94 | 3.0 | 474 | 0.7401 | 0.8761 |
| 0.6491 | 4.0 | 633 | 0.4772 | 0.9118 |
| 0.5516 | 5.0 | 791 | 0.3857 | 0.9242 |
| 0.5164 | 5.99 | 948 | 0.3609 | 0.9286 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0