metadata

license: apache-2.0
base_model: facebook/deit-small-patch16-224
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: hushem_1x_deit_small_adamax_00001_fold1
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: imagefolder
          type: imagefolder
          config: default
          split: test
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.6

hushem_1x_deit_small_adamax_00001_fold1

This model is a fine-tuned version of facebook/deit-small-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 1.1270
Accuracy: 0.6

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: 1e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
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
No log	1.0	6	1.3199	0.3333
1.3414	2.0	12	1.2923	0.4667
1.3414	3.0	18	1.2886	0.4667
1.0791	4.0	24	1.2761	0.4667
0.9244	5.0	30	1.2453	0.4889
0.9244	6.0	36	1.2252	0.4667
0.7694	7.0	42	1.2158	0.5111
0.7694	8.0	48	1.2163	0.4667
0.6552	9.0	54	1.2081	0.5111
0.5314	10.0	60	1.1883	0.5556
0.5314	11.0	66	1.1802	0.5556
0.4407	12.0	72	1.1737	0.5778
0.4407	13.0	78	1.1623	0.6222
0.3864	14.0	84	1.1625	0.6222
0.3093	15.0	90	1.1653	0.6222
0.3093	16.0	96	1.1658	0.6222
0.2597	17.0	102	1.1519	0.6444
0.2597	18.0	108	1.1466	0.6222
0.2099	19.0	114	1.1591	0.6
0.1766	20.0	120	1.1509	0.5778
0.1766	21.0	126	1.1488	0.5778
0.1537	22.0	132	1.1482	0.5778
0.1537	23.0	138	1.1427	0.6222
0.1244	24.0	144	1.1370	0.6
0.103	25.0	150	1.1285	0.6
0.103	26.0	156	1.1323	0.6
0.089	27.0	162	1.1268	0.6
0.089	28.0	168	1.1377	0.6
0.0777	29.0	174	1.1346	0.6
0.068	30.0	180	1.1274	0.6
0.068	31.0	186	1.1199	0.6
0.0597	32.0	192	1.1245	0.6
0.0597	33.0	198	1.1296	0.6
0.0547	34.0	204	1.1270	0.6
0.0493	35.0	210	1.1241	0.6
0.0493	36.0	216	1.1250	0.6
0.0441	37.0	222	1.1253	0.6
0.0441	38.0	228	1.1296	0.6
0.0409	39.0	234	1.1287	0.6
0.0405	40.0	240	1.1275	0.6
0.0405	41.0	246	1.1272	0.6
0.0391	42.0	252	1.1270	0.6
0.0391	43.0	258	1.1270	0.6
0.0395	44.0	264	1.1270	0.6
0.0377	45.0	270	1.1270	0.6
0.0377	46.0	276	1.1270	0.6
0.0388	47.0	282	1.1270	0.6
0.0388	48.0	288	1.1270	0.6
0.0366	49.0	294	1.1270	0.6
0.0396	50.0	300	1.1270	0.6

Framework versions

Transformers 4.35.0
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1