|
--- |
|
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 |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# 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](https://huggingface.co/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 |
|
|
