convnext-tiny-224_flyswot

This model was trained from scratch on the image_folder dataset. It achieves the following results on the evaluation set:

• Loss: 0.5319
• F1: 0.9756

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: 2e-05
• train_batch_size: 32
• eval_batch_size: 32
• seed: 666
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 50
• mixed_precision_training: Native AMP
• label_smoothing_factor: 0.1

Training results

Training Loss	Epoch	Step	Validation Loss	F1
No log	1.0	52	0.5478	0.9720
No log	2.0	104	0.5432	0.9709
No log	3.0	156	0.5437	0.9731
No log	4.0	208	0.5433	0.9712
No log	5.0	260	0.5373	0.9745
No log	6.0	312	0.5371	0.9756
No log	7.0	364	0.5381	0.9737
No log	8.0	416	0.5376	0.9744
No log	9.0	468	0.5431	0.9694
0.4761	10.0	520	0.5468	0.9725
0.4761	11.0	572	0.5404	0.9755
0.4761	12.0	624	0.5481	0.9669
0.4761	13.0	676	0.5432	0.9687
0.4761	14.0	728	0.5409	0.9731
0.4761	15.0	780	0.5403	0.9737
0.4761	16.0	832	0.5393	0.9737
0.4761	17.0	884	0.5412	0.9719
0.4761	18.0	936	0.5433	0.9674
0.4761	19.0	988	0.5367	0.9755
0.4705	20.0	1040	0.5389	0.9737
0.4705	21.0	1092	0.5396	0.9737
0.4705	22.0	1144	0.5514	0.9683
0.4705	23.0	1196	0.5550	0.9617
0.4705	24.0	1248	0.5428	0.9719
0.4705	25.0	1300	0.5371	0.9719
0.4705	26.0	1352	0.5455	0.9719
0.4705	27.0	1404	0.5409	0.9680
0.4705	28.0	1456	0.5345	0.9756
0.4696	29.0	1508	0.5381	0.9756
0.4696	30.0	1560	0.5387	0.9705
0.4696	31.0	1612	0.5540	0.9605
0.4696	32.0	1664	0.5467	0.9706
0.4696	33.0	1716	0.5322	0.9756
0.4696	34.0	1768	0.5325	0.9756
0.4696	35.0	1820	0.5305	0.9737
0.4696	36.0	1872	0.5305	0.9769
0.4696	37.0	1924	0.5345	0.9756
0.4696	38.0	1976	0.5315	0.9737
0.4699	39.0	2028	0.5333	0.9756
0.4699	40.0	2080	0.5316	0.9756
0.4699	41.0	2132	0.5284	0.9756
0.4699	42.0	2184	0.5325	0.9756
0.4699	43.0	2236	0.5321	0.9756
0.4699	44.0	2288	0.5322	0.9756
0.4699	45.0	2340	0.5323	0.9756
0.4699	46.0	2392	0.5318	0.9756
0.4699	47.0	2444	0.5329	0.9756
0.4699	48.0	2496	0.5317	0.9756
0.4701	49.0	2548	0.5317	0.9756
0.4701	50.0	2600	0.5319	0.9756

Framework versions

• Transformers 4.17.0
• Pytorch 1.10.0+cu111
• Datasets 2.0.0
• Tokenizers 0.11.6