metadata
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
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 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