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

Loss: 0.8418
Accuracy: 0.8780

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: 0.0001
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
1.4959	1.0	28	1.3943	0.2439
1.4016	2.0	56	1.1344	0.4146
0.8658	3.0	84	0.7965	0.7073
0.4771	4.0	112	0.8323	0.7073
0.2251	5.0	140	0.3450	0.8537
0.161	6.0	168	1.1238	0.5854
0.122	7.0	196	0.5699	0.8780
0.0493	8.0	224	1.1342	0.6585
0.0526	9.0	252	1.0124	0.8293
0.0543	10.0	280	1.4922	0.8537
0.0179	11.0	308	0.4348	0.9024
0.001	12.0	336	0.7229	0.8293
0.0002	13.0	364	0.6260	0.8780
0.0001	14.0	392	0.6381	0.8780
0.0001	15.0	420	0.6479	0.8780
0.0001	16.0	448	0.6572	0.8780
0.0001	17.0	476	0.6669	0.8780
0.0	18.0	504	0.6750	0.8780
0.0	19.0	532	0.6816	0.8780
0.0	20.0	560	0.6897	0.8780
0.0	21.0	588	0.6973	0.8780
0.0	22.0	616	0.7042	0.8780
0.0	23.0	644	0.7114	0.8780
0.0	24.0	672	0.7182	0.8780
0.0	25.0	700	0.7246	0.8780
0.0	26.0	728	0.7318	0.8780
0.0	27.0	756	0.7392	0.8780
0.0	28.0	784	0.7454	0.8780
0.0	29.0	812	0.7524	0.8780
0.0	30.0	840	0.7588	0.8780
0.0	31.0	868	0.7650	0.8780
0.0	32.0	896	0.7711	0.8780
0.0	33.0	924	0.7761	0.8780
0.0	34.0	952	0.7832	0.8780
0.0	35.0	980	0.7888	0.8780
0.0	36.0	1008	0.7948	0.8780
0.0	37.0	1036	0.8020	0.8780
0.0	38.0	1064	0.8075	0.8780
0.0	39.0	1092	0.8124	0.8780
0.0	40.0	1120	0.8170	0.8780
0.0	41.0	1148	0.8223	0.8780
0.0	42.0	1176	0.8266	0.8780
0.0	43.0	1204	0.8300	0.8780
0.0	44.0	1232	0.8327	0.8780
0.0	45.0	1260	0.8359	0.8780
0.0	46.0	1288	0.8390	0.8780
0.0	47.0	1316	0.8409	0.8780
0.0	48.0	1344	0.8418	0.8780
0.0	49.0	1372	0.8418	0.8780
0.0	50.0	1400	0.8418	0.8780

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0

hkivancoral/hushem_5x_deit_tiny_rms_0001_fold5

hushem_5x_deit_tiny_rms_0001_fold5

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

hkivancoral/
hushem_5x_deit_tiny_rms_0001_fold5