resnet-50-finetuned-oxfordflowers

This model is a fine-tuned version of microsoft/resnet-50 on the oxford102_flower_dataset dataset. It achieves the following results on the evaluation set:

• Loss: 0.6561
• Accuracy: 0.8330
• Precision: 0.8531
• Recall: 0.8330
• F1: 0.8319

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: 0.001
• train_batch_size: 32
• eval_batch_size: 32
• 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: linear
• num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
4.4813	1.0	32	4.1934	0.3176	0.3522	0.3176	0.2599
2.6507	2.0	64	1.8716	0.5382	0.5792	0.5382	0.4930
1.257	3.0	96	1.0998	0.7216	0.7663	0.7216	0.7085
0.5333	4.0	128	0.9724	0.7422	0.7875	0.7422	0.7296
0.2506	5.0	160	0.8243	0.7627	0.7975	0.7627	0.7566
0.0689	6.0	192	0.7067	0.8147	0.8482	0.8147	0.8111
0.0325	7.0	224	0.6370	0.8206	0.8428	0.8206	0.8175
0.0132	8.0	256	0.5774	0.8412	0.8617	0.8412	0.8389
0.0117	9.0	288	0.5469	0.8559	0.8726	0.8559	0.8542
0.0066	10.0	320	0.5384	0.8608	0.8722	0.8608	0.8575
0.0072	11.0	352	0.5246	0.8686	0.8783	0.8686	0.8650
0.0068	12.0	384	0.5130	0.8716	0.8790	0.8716	0.8679
0.0045	13.0	416	0.5038	0.8716	0.8814	0.8716	0.8691
0.0025	14.0	448	0.5486	0.85	0.8627	0.85	0.8448
0.0029	15.0	480	0.4992	0.8637	0.8736	0.8637	0.8619

Framework versions

• Transformers 4.47.1
• Pytorch 2.5.1+cu121
• Datasets 3.2.0
• Tokenizers 0.21.0