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

Loss: 0.6440
Accuracy: 0.7485

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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	19	1.0763	0.4386
No log	2.0	38	0.9918	0.5322
No log	3.0	57	0.8919	0.6725
No log	4.0	76	0.8088	0.7135
No log	5.0	95	0.7502	0.7368
No log	6.0	114	0.7037	0.7310
No log	7.0	133	0.6792	0.7427
No log	8.0	152	0.6507	0.7368
No log	9.0	171	0.6440	0.7485
No log	10.0	190	0.6415	0.7485

Framework versions

Transformers 4.28.0
Pytorch 2.0.0+cu118
Datasets 2.12.0
Tokenizers 0.13.3

Elsospi/convnext-large-224-finetuned-eurosat

convnext-large-224-finetuned-eurosat

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Elsospi/
convnext-large-224-finetuned-eurosat