cvt-21-384-22k-finetuned-PinnatelyCompound

This model is a fine-tuned version of microsoft/cvt-21-384-22k on the imagefolder dataset. It achieves the following results on the evaluation set:

• Loss: 0.0064
• Accuracy: 0.9955

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: 40
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	23	0.2918	0.8973
No log	2.0	46	0.1656	0.9330
No log	3.0	69	0.0529	0.9821
No log	4.0	92	0.0144	0.9955
No log	5.0	115	0.0266	0.9911
No log	6.0	138	0.0244	0.9955
No log	7.0	161	0.0144	0.9955
No log	8.0	184	0.0154	0.9955
No log	9.0	207	0.0188	0.9911
No log	10.0	230	0.0094	0.9955
No log	11.0	253	0.0055	1.0
No log	12.0	276	0.0026	1.0
No log	13.0	299	0.0057	1.0
No log	14.0	322	0.0079	0.9955
No log	15.0	345	0.0026	1.0
No log	16.0	368	0.0017	1.0
No log	17.0	391	0.0044	0.9955
No log	18.0	414	0.0038	1.0
No log	19.0	437	0.0120	0.9911
No log	20.0	460	0.0005	1.0
No log	21.0	483	0.0019	1.0
0.2553	22.0	506	0.0020	1.0
0.2553	23.0	529	0.0026	1.0
0.2553	24.0	552	0.0053	0.9955
0.2553	25.0	575	0.0009	1.0
0.2553	26.0	598	0.0008	1.0
0.2553	27.0	621	0.0016	1.0
0.2553	28.0	644	0.0010	1.0
0.2553	29.0	667	0.0008	1.0
0.2553	30.0	690	0.0064	0.9955

Framework versions

• Transformers 4.38.1
• Pytorch 1.10.0+cu111
• Datasets 2.17.1
• Tokenizers 0.15.2