metadata

license: apache-2.0
base_model: microsoft/swinv2-tiny-patch4-window8-256
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: swinv2-tiny-patch4-window8-256-finetuned-galaxy10-decals
    results: []

swinv2-tiny-patch4-window8-256-finetuned-galaxy10-decals

This model is a fine-tuned version of microsoft/swinv2-tiny-patch4-window8-256 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.4357
Accuracy: 0.8585

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: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.318	0.9940	124	1.0409	0.6359
0.9268	1.9960	249	0.7164	0.7497
0.8221	2.9980	374	0.6210	0.7875
0.7276	4.0	499	0.5564	0.8162
0.6425	4.9940	623	0.5226	0.8162
0.6518	5.9960	748	0.5377	0.8185
0.6096	6.9980	873	0.5341	0.8219
0.6282	8.0	998	0.4718	0.8399
0.5394	8.9940	1122	0.5113	0.8281
0.5718	9.9960	1247	0.5019	0.8292
0.5507	10.9980	1372	0.4545	0.8461
0.4921	12.0	1497	0.4613	0.8416
0.5571	12.9940	1621	0.4587	0.8416
0.512	13.9960	1746	0.4673	0.8512
0.4855	14.9980	1871	0.4641	0.8489
0.4895	16.0	1996	0.4556	0.8450
0.4809	16.9940	2120	0.4317	0.8523
0.4785	17.9960	2245	0.4338	0.8534
0.444	18.9980	2370	0.4357	0.8579
0.4255	19.8798	2480	0.4357	0.8585

Framework versions

Transformers 4.40.1
Pytorch 1.12.1+cu116
Datasets 2.19.0
Tokenizers 0.19.1