uisikdag/weed_resnet_imbalanced

weeds_hfclass20

Model is trained on imbalanced dataset/ .8 .1 .1 split/ 224x224 resized

Dataset: https://www.kaggle.com/datasets/vbookshelf/v2-plant-seedlings-dataset

This model is a fine-tuned version of microsoft/resnet-152 on the imagefolder dataset. It achieves the following results on the evaluation set:

• Loss: 0.4375
• Accuracy: 0.8696

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: 16
• eval_batch_size: 16
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 64
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
2.444	1.0	69	2.4226	0.2018
2.3378	2.0	138	2.2755	0.3268
1.9474	3.0	207	1.8114	0.5286
1.4306	4.0	276	1.2129	0.6571
0.9848	5.0	345	0.8457	0.7536
0.8489	6.0	414	0.6503	0.8
0.7054	7.0	483	0.5202	0.8411
0.6404	8.0	552	0.5067	0.8607
0.5939	9.0	621	0.4575	0.8589
0.6365	10.0	690	0.4375	0.8696

Framework versions

• Transformers 4.26.1
• Pytorch 1.13.1+cu117
• Datasets 2.10.1
• Tokenizers 0.13.2