|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- imagefolder |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: weeds_hfclass20 |
|
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: 0.8696428571428572 |
|
--- |
|
|
|
<!-- 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_hfclass20 |
|
Model is trained on imbalanced dataset/ .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](https://huggingface.co/microsoft/resnet-152) on the imagefolder dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4375 |
|
- Accuracy: 0.8696 |
|
|
|
## 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 2.444 | 1.0 | 69 | 2.4226 | 0.2018 | |
|
| 2.3378 | 2.0 | 138 | 2.2755 | 0.3268 | |
|
| 1.9474 | 3.0 | 207 | 1.8114 | 0.5286 | |
|
| 1.4306 | 4.0 | 276 | 1.2129 | 0.6571 | |
|
| 0.9848 | 5.0 | 345 | 0.8457 | 0.7536 | |
|
| 0.8489 | 6.0 | 414 | 0.6503 | 0.8 | |
|
| 0.7054 | 7.0 | 483 | 0.5202 | 0.8411 | |
|
| 0.6404 | 8.0 | 552 | 0.5067 | 0.8607 | |
|
| 0.5939 | 9.0 | 621 | 0.4575 | 0.8589 | |
|
| 0.6365 | 10.0 | 690 | 0.4375 | 0.8696 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.26.1 |
|
- Pytorch 1.13.1+cu117 |
|
- Datasets 2.10.1 |
|
- Tokenizers 0.13.2 |
|
|
