Output-prova_melanoma

Oppoizer/Output-prova_melanoma

Output-prova_melanoma is a image classification model from Oppoizer. Use it when you need a label for an image. It is set up for transformers. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Image Classification
Library: transformers
License: apache-2.0
Model type: vit
Access: Public
Created: Jun 7, 2023
Updated: Jan 9, 2024
SHA: f9dcba1d

Datasets

imagefolder

Model card

From the Hugging Face model README

Output-prova_melanoma

This model is a fine-tuned version of UnipaPolitoUnimore/vit-large-patch32-384-melanoma on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 0.2202
Accuracy: 0.9467

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: 1.5e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 40

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.4501	1.0	47	0.2094	0.9667
0.5554	2.0	94	0.2010	0.9733
0.5299	3.0	141	0.1595	0.9733
0.0854	4.0	188	0.1529	0.9667
0.2766	5.0	235	0.1466	0.9667
0.3158	6.0	282	0.1916	0.96
0.1322	7.0	329	0.1924	0.9733
0.065	8.0	376	0.1905	0.9533
0.1565	9.0	423	0.2025	0.9467
0.1296	10.0	470	0.2367	0.9333
0.2448	11.0	517	0.2255	0.94
0.067	12.0	564	0.2315	0.94
0.0764	13.0	611	0.2479	0.9467
0.1472	14.0	658	0.2599	0.9333
0.0483	15.0	705	0.1911	0.9533
0.0961	16.0	752	0.1869	0.9533
0.1146	17.0	799	0.2355	0.9333
0.2117	18.0	846	0.1930	0.94
0.2859	19.0	893	0.1902	0.9467
0.0798	20.0	940	0.2436	0.9333
0.16	21.0	987	0.2341	0.94
0.1968	22.0	1034	0.3552	0.9067
0.1049	23.0	1081	0.2541	0.9267
0.1102	24.0	1128	0.1839	0.9467
0.3039	25.0	1175	0.2269	0.9333
0.1188	26.0	1222	0.2063	0.9533
0.2008	27.0	1269	0.1972	0.94
0.1113	28.0	1316	0.2157	0.94
0.1377	29.0	1363	0.2031	0.9533
0.042	30.0	1410	0.2124	0.9533
0.0841	31.0	1457	0.2174	0.94
0.046	32.0	1504	0.2136	0.9467
0.1309	33.0	1551	0.1981	0.96
0.1207	34.0	1598	0.2334	0.94
0.1216	35.0	1645	0.2238	0.94
0.0518	36.0	1692	0.2441	0.9467
0.0852	37.0	1739	0.2243	0.9467
0.0853	38.0	1786	0.2028	0.9533
0.055	39.0	1833	0.2124	0.9467
0.0646	40.0	1880	0.2202	0.9467

Framework versions

Transformers 4.30.0.dev0
Pytorch 1.13.1+cu116
Datasets 2.11.0
Tokenizers 0.13.3

Task: Image Classification
Library: transformers
Type: vit
License: apache-2.0
Created: Jun 7, 2023
Updated: Jan 9, 2024