metadata

license: apache-2.0
base_model: facebook/deit-small-patch16-224
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: hushem_5x_deit_small_sgd_001_fold4
    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: 0.5

hushem_5x_deit_small_sgd_001_fold4

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: 1.0586
Accuracy: 0.5

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: 0.001
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
1.487	1.0	28	1.4172	0.3095
1.4655	2.0	56	1.3829	0.3333
1.3519	3.0	84	1.3645	0.2619
1.3235	4.0	112	1.3524	0.2619
1.3019	5.0	140	1.3421	0.2857
1.2683	6.0	168	1.3287	0.2857
1.2448	7.0	196	1.3147	0.2857
1.2154	8.0	224	1.3011	0.2619
1.1886	9.0	252	1.2876	0.3571
1.1547	10.0	280	1.2739	0.3810
1.1374	11.0	308	1.2618	0.3810
1.1111	12.0	336	1.2488	0.3810
1.1298	13.0	364	1.2398	0.4048
1.0797	14.0	392	1.2302	0.4048
1.0414	15.0	420	1.2217	0.4286
1.061	16.0	448	1.2120	0.4286
1.0634	17.0	476	1.2016	0.4524
1.0054	18.0	504	1.1928	0.4524
0.9762	19.0	532	1.1844	0.4524
1.0106	20.0	560	1.1764	0.4524
0.9235	21.0	588	1.1685	0.4524
0.9458	22.0	616	1.1599	0.4762
0.9326	23.0	644	1.1543	0.5
0.9222	24.0	672	1.1465	0.5
0.8846	25.0	700	1.1391	0.5
0.8795	26.0	728	1.1307	0.4762
0.8711	27.0	756	1.1242	0.5238
0.8921	28.0	784	1.1184	0.5238
0.8796	29.0	812	1.1133	0.5238
0.8567	30.0	840	1.1054	0.5238
0.8632	31.0	868	1.1011	0.5238
0.8179	32.0	896	1.0965	0.5238
0.8418	33.0	924	1.0917	0.5238
0.8097	34.0	952	1.0866	0.5238
0.8474	35.0	980	1.0818	0.5238
0.7989	36.0	1008	1.0776	0.5238
0.7935	37.0	1036	1.0750	0.5238
0.8104	38.0	1064	1.0725	0.5238
0.8018	39.0	1092	1.0698	0.5238
0.797	40.0	1120	1.0673	0.5238
0.8004	41.0	1148	1.0654	0.5238
0.775	42.0	1176	1.0641	0.5
0.7606	43.0	1204	1.0623	0.5
0.7649	44.0	1232	1.0613	0.5
0.7627	45.0	1260	1.0601	0.5
0.7807	46.0	1288	1.0595	0.5
0.7697	47.0	1316	1.0588	0.5
0.7683	48.0	1344	1.0586	0.5
0.783	49.0	1372	1.0586	0.5
0.7862	50.0	1400	1.0586	0.5

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0