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

Loss: nan
Accuracy: 0.4835

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: 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: 5

Training results

Epoch	Step	Validation Loss	Accuracy
0.99	73	nan	0.4835
1.99	147	nan	0.4835
3.0	221	nan	0.4835
4.0	295	nan	0.4835
4.95	365	nan	0.4835

Framework versions

Transformers 4.36.2
Pytorch 1.11.0+cu102
Datasets 2.16.0
Tokenizers 0.15.0

alirzb/S1_M1_R3_beit_42507359

S1_M1_R3_beit_42507359

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

alirzb/
S1_M1_R3_beit_42507359