weeds_hfclass12

Model is trained on balanced dataset/ 250 image per class/ .8 .1 .1 split/ 224x224 resized

Dataset: https://www.kaggle.com/datasets/vbookshelf/v2-plant-seedlings-dataset

This model is a fine-tuned version of microsoft/beit-base-patch16-224-pt22k-ft22k on the imagefolder dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1257
  • Accuracy: 0.96

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: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.6013 0.99 37 0.7579 0.8067
0.3887 1.99 74 0.2834 0.9033
0.2846 2.99 111 0.2767 0.9
0.2086 3.99 148 0.2642 0.9067
0.1664 4.99 185 0.2016 0.9333
0.168 5.99 222 0.1498 0.9533
0.1159 6.99 259 0.1607 0.9533
0.1195 7.99 296 0.1719 0.9467
0.1013 8.99 333 0.1442 0.9533
0.0939 9.99 370 0.1257 0.96

Framework versions

  • Transformers 4.26.1
  • Pytorch 1.13.1+cu117
  • Datasets 2.10.1
  • Tokenizers 0.13.2
Downloads last month
14
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Space using uisikdag/weed_beit_balanced 1

Evaluation results