7-classifier-finetuned-padchest

sbottazzi/7-classifier-finetuned-padchest

7-classifier-finetuned-padchest is a image classification model from sbottazzi. 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: Mar 28, 2024
Updated: Mar 29, 2024
SHA: d13178ae

Datasets

imagefolder

Model card

From the Hugging Face model README

7-classifier-finetuned-padchest

This model is a fine-tuned version of nickmuchi/vit-finetuned-chest-xray-pneumonia on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 0.7844
F1: 0.7449

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	F1
2.0948	1.0	18	1.9801	0.1856
1.916	2.0	36	1.7571	0.3242
1.6873	3.0	54	1.5333	0.4149
1.4576	4.0	72	1.3515	0.4656
1.2824	5.0	90	1.2288	0.4936
1.2004	6.0	108	1.1050	0.5462
1.1264	7.0	126	1.0643	0.5713
1.0149	8.0	144	1.0612	0.5718
0.9839	9.0	162	0.9897	0.6266
0.9001	10.0	180	0.9542	0.6710
0.9093	11.0	198	0.8993	0.6811
0.8824	12.0	216	0.8877	0.7018
0.8237	13.0	234	0.8970	0.7071
0.8446	14.0	252	0.8619	0.7084
0.7766	15.0	270	0.8271	0.7331
0.7405	16.0	288	0.8516	0.7237
0.7672	17.0	306	0.8036	0.7223
0.7149	18.0	324	0.8188	0.7186
0.7	19.0	342	0.8391	0.7274
0.7011	20.0	360	0.7922	0.7424
0.695	21.0	378	0.8065	0.7394
0.6655	22.0	396	0.7783	0.7473
0.6377	23.0	414	0.7977	0.7296
0.6884	24.0	432	0.7724	0.7387
0.614	25.0	450	0.8372	0.7351
0.6008	26.0	468	0.8229	0.7277
0.6402	27.0	486	0.7958	0.7300
0.592	28.0	504	0.8222	0.7264
0.5774	29.0	522	0.7613	0.7511
0.584	30.0	540	0.7866	0.7377
0.558	31.0	558	0.8298	0.7351
0.5871	32.0	576	0.7727	0.7494
0.5608	33.0	594	0.7753	0.7695
0.5385	34.0	612	0.7585	0.7575
0.5461	35.0	630	0.7664	0.7521
0.506	36.0	648	0.7624	0.7581
0.5132	37.0	666	0.7914	0.7347
0.5083	38.0	684	0.7913	0.7425
0.5042	39.0	702	0.7704	0.7556
0.4539	40.0	720	0.7590	0.7578
0.4714	41.0	738	0.7912	0.7503
0.4681	42.0	756	0.7838	0.7420
0.4482	43.0	774	0.7781	0.7345
0.4535	44.0	792	0.7823	0.7415
0.4284	45.0	810	0.8104	0.7449
0.436	46.0	828	0.7829	0.7421
0.4526	47.0	846	0.7932	0.7567
0.4672	48.0	864	0.7827	0.7411
0.4171	49.0	882	0.7835	0.7447
0.4126	50.0	900	0.7844	0.7449

Framework versions

Transformers 4.28.0.dev0
Pytorch 2.0.0+cu117
Datasets 2.18.0
Tokenizers 0.13.3

Task: Image Classification
Library: transformers
Type: vit
License: apache-2.0
Created: Mar 28, 2024
Updated: Mar 29, 2024