convnextv2-base-1k-224-for-pre_evaluation

This model is a fine-tuned version of facebook/convnextv2-base-1k-224 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 1.3599
• Accuracy: 0.4190

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: 32
• eval_batch_size: 32
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 128
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.6	1.0	16	1.5316	0.2961
1.5084	2.0	32	1.5061	0.2849
1.5134	3.0	48	1.4968	0.3240
1.4663	4.0	64	1.4607	0.3352
1.4046	5.0	80	1.4509	0.3268
1.4085	6.0	96	1.4423	0.3883
1.3443	7.0	112	1.4005	0.4022
1.3025	8.0	128	1.3599	0.4190
1.2627	9.0	144	1.3638	0.3911
1.2099	10.0	160	1.4058	0.3492
1.2086	11.0	176	1.4431	0.3408
1.1393	12.0	192	1.4143	0.3492
1.1039	13.0	208	1.4305	0.3883
1.0551	14.0	224	1.5203	0.3520
1.0368	15.0	240	1.5117	0.3324
0.9753	16.0	256	1.4545	0.3771
0.938	17.0	272	1.5396	0.3352
0.899	18.0	288	1.5770	0.3408
0.8629	19.0	304	1.7106	0.3128
0.8674	20.0	320	1.5864	0.3352
0.7789	21.0	336	1.6129	0.3408
0.7426	22.0	352	1.6353	0.3603
0.7677	23.0	368	1.6793	0.3464
0.7172	24.0	384	1.6759	0.3575
0.6809	25.0	400	1.7013	0.3659
0.6619	26.0	416	1.7108	0.3631
0.6656	27.0	432	1.7327	0.3715
0.6258	28.0	448	1.7378	0.3547
0.6173	29.0	464	1.7461	0.3603
0.6214	30.0	480	1.7475	0.3520

Framework versions

• Transformers 4.33.1
• Pytorch 2.0.1+cu118
• Datasets 2.14.5
• Tokenizers 0.13.3