metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: weeds_hfclass18
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: 0.7766666666666666
weeds_hfclass18
Model is trained on balanced dataset/250 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/resnet-152 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.2397
- Accuracy: 0.7767
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 |
|---|---|---|---|---|
| 2.4803 | 0.99 | 37 | 2.4724 | 0.1133 |
| 2.4464 | 1.99 | 74 | 2.4305 | 0.2967 |
| 2.3843 | 2.99 | 111 | 2.3658 | 0.4233 |
| 2.3018 | 3.99 | 148 | 2.2287 | 0.5067 |
| 2.1075 | 4.99 | 185 | 2.0144 | 0.5967 |
| 1.8743 | 5.99 | 222 | 1.7228 | 0.65 |
| 1.7114 | 6.99 | 259 | 1.5487 | 0.6833 |
| 1.5345 | 7.99 | 296 | 1.3920 | 0.7267 |
| 1.4471 | 8.99 | 333 | 1.2914 | 0.7333 |
| 1.3994 | 9.99 | 370 | 1.2397 | 0.7767 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.10.1
- Tokenizers 0.13.2