cards_bottom_left_swin-tiny-patch4-window7-224-finetuned-v2_more_Data

This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

• Loss: 1.0009
• Accuracy: 0.5928

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: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.559	1.0	1362	1.3402	0.4189
1.5165	2.0	2725	1.2308	0.4647
1.484	3.0	4087	1.1676	0.4954
1.5037	4.0	5450	1.1206	0.5198
1.4489	5.0	6812	1.1162	0.5284
1.4335	6.0	8175	1.1395	0.5047
1.4281	7.0	9537	1.0606	0.5445
1.4219	8.0	10900	1.0754	0.5408
1.3935	9.0	12262	1.0285	0.5604
1.3542	10.0	13625	1.0497	0.5453
1.3761	11.0	14987	1.0535	0.5450
1.3824	12.0	16350	1.0268	0.5591
1.3709	13.0	17712	1.0015	0.5690
1.3361	14.0	19075	1.0266	0.5595
1.3673	15.0	20437	0.9988	0.5772
1.376	16.0	21800	0.9950	0.5744
1.3486	17.0	23162	0.9837	0.5784
1.3333	18.0	24525	0.9771	0.5827
1.347	19.0	25887	0.9895	0.5770
1.3381	20.0	27250	0.9709	0.5820
1.3385	21.0	28612	0.9704	0.5833
1.336	22.0	29975	0.9646	0.5885
1.3372	23.0	31337	0.9653	0.5879
1.2979	24.0	32700	0.9867	0.5814
1.2948	25.0	34062	0.9633	0.5870
1.2767	26.0	35425	0.9578	0.5877
1.3012	27.0	36787	0.9709	0.5867
1.2667	28.0	38150	0.9648	0.5899
1.3	29.0	39512	0.9560	0.5930
1.2735	30.0	40875	0.9595	0.5949
1.2895	31.0	42237	0.9851	0.5809
1.2234	32.0	43600	0.9601	0.5931
1.2212	33.0	44962	0.9800	0.5917
1.2483	34.0	46325	0.9662	0.5982
1.2507	35.0	47687	0.9657	0.5910
1.2539	36.0	49050	0.9954	0.5783
1.2491	37.0	50412	0.9718	0.5924
1.2397	38.0	51775	0.9769	0.5930
1.1903	39.0	53137	0.9717	0.5945
1.2475	40.0	54500	0.9995	0.5855
1.2371	41.0	55862	0.9861	0.5935
1.2561	42.0	57225	0.9856	0.5958
1.2069	43.0	58587	0.9913	0.5892
1.2188	44.0	59950	0.9902	0.5950
1.1732	45.0	61312	0.9892	0.5949
1.1705	46.0	62675	0.9991	0.5914
1.18	47.0	64037	0.9952	0.5925
1.2353	48.0	65400	0.9999	0.5933
1.2057	49.0	66762	1.0001	0.5920
1.1833	49.98	68100	1.0009	0.5928

Framework versions

• Transformers 4.37.2
• Pytorch 2.0.1+cu117
• Datasets 2.17.0
• Tokenizers 0.15.2