metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: weeds_hfclass11
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: test
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9566666666666667
weeds_hfclass11
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 google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.3603
- Accuracy: 0.9567
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 |
|---|---|---|---|---|
| 2.3089 | 0.99 | 37 | 2.0422 | 0.7133 |
| 1.4465 | 1.99 | 74 | 1.2227 | 0.8767 |
| 0.8455 | 2.99 | 111 | 0.8121 | 0.9067 |
| 0.6579 | 3.99 | 148 | 0.6161 | 0.9267 |
| 0.5163 | 4.99 | 185 | 0.5031 | 0.94 |
| 0.4374 | 5.99 | 222 | 0.4078 | 0.9633 |
| 0.3912 | 6.99 | 259 | 0.4134 | 0.9467 |
| 0.358 | 7.99 | 296 | 0.4207 | 0.9233 |
| 0.3509 | 8.99 | 333 | 0.3768 | 0.95 |
| 0.3288 | 9.99 | 370 | 0.3603 | 0.9567 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.10.1
- Tokenizers 0.13.2