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eunsxx/
finetuned-pokemon

Name: finetuned-pokemon
Availability: InStock

generated_from_trainer

apache-2.0

autotrain_compatible

endpoints_compatible

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finetuned-pokemon

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the pokemon_images dataset. It achieves the following results on the evaluation set:

Loss: 0.5483
Accuracy: 0.8849

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: 0.0002
train_batch_size: 16
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
4.2294	0.18	100	4.2177	0.2408
3.3443	0.35	200	3.3392	0.4415
2.6829	0.53	300	2.5744	0.6848
2.1544	0.71	400	1.9695	0.7430
1.5132	0.88	500	1.4847	0.7761
0.8297	1.06	600	1.1503	0.7974
0.6333	1.23	700	0.8776	0.8349
0.4634	1.41	800	0.7625	0.8462
0.4646	1.59	900	0.7139	0.8293
0.4092	1.76	1000	0.6812	0.8368
0.4207	1.94	1100	0.6669	0.8330
0.2222	2.12	1200	0.6346	0.8449
0.201	2.29	1300	0.5713	0.8574
0.2236	2.47	1400	0.5948	0.8587
0.2694	2.65	1500	0.5563	0.8680
0.1744	2.82	1600	0.5784	0.8593
0.2472	3.0	1700	0.6019	0.8518
0.0779	3.17	1800	0.5899	0.8693
0.0966	3.35	1900	0.5861	0.8587
0.0962	3.53	2000	0.5981	0.8630
0.1396	3.7	2100	0.6345	0.8455
0.083	3.88	2200	0.5822	0.8668
0.0649	4.06	2300	0.6148	0.8530
0.0476	4.23	2400	0.5906	0.8687
0.1119	4.41	2500	0.5902	0.8649
0.0748	4.59	2600	0.5671	0.8780
0.0934	4.76	2700	0.5834	0.8724
0.0648	4.94	2800	0.6095	0.8580
0.051	5.11	2900	0.6209	0.8574
0.0341	5.29	3000	0.5671	0.8780
0.1553	5.47	3100	0.5838	0.8730
0.0425	5.64	3200	0.5808	0.8712
0.0269	5.82	3300	0.5734	0.8693
0.1104	6.0	3400	0.5823	0.8718
0.1136	6.17	3500	0.5698	0.8774
0.0276	6.35	3600	0.5996	0.8699
0.0408	6.53	3700	0.5642	0.8768
0.0147	6.7	3800	0.5913	0.8762
0.0395	6.88	3900	0.5838	0.8630
0.014	7.05	4000	0.5722	0.8762
0.025	7.23	4100	0.5749	0.8768
0.0536	7.41	4200	0.5693	0.8806
0.0602	7.58	4300	0.5483	0.8849
0.0618	7.76	4400	0.5597	0.8774
0.0447	7.94	4500	0.5539	0.8812
0.0811	8.11	4600	0.5692	0.8762
0.0514	8.29	4700	0.5665	0.8812
0.0635	8.47	4800	0.5737	0.8793
0.0474	8.64	4900	0.5817	0.8799
0.03	8.82	5000	0.5833	0.8774
0.0224	8.99	5100	0.5743	0.8818
0.0205	9.17	5200	0.5794	0.8831
0.0326	9.35	5300	0.5838	0.8806
0.0617	9.52	5400	0.5777	0.8812
0.019	9.7	5500	0.5781	0.8806
0.0412	9.88	5600	0.5797	0.8806

Framework versions

Transformers 4.30.1
Pytorch 2.0.1+cu118
Datasets 2.12.0
Tokenizers 0.13.3

eunsxx/finetuned-pokemon

finetuned-pokemon

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

eunsxx/
finetuned-pokemon