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: 0.8678571428571429
weeds_hfclass18
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: 0.4372
- Accuracy: 0.8679
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 |
|---|---|---|---|---|
| 2.4335 | 1.0 | 69 | 2.4087 | 0.2375 |
| 2.3043 | 2.0 | 138 | 2.2215 | 0.3339 |
| 1.8342 | 3.0 | 207 | 1.6984 | 0.5786 |
| 1.4059 | 4.0 | 276 | 1.1954 | 0.6804 |
| 1.0081 | 5.0 | 345 | 0.8756 | 0.7482 |
| 0.8916 | 6.0 | 414 | 0.6818 | 0.8232 |
| 0.7313 | 7.0 | 483 | 0.5369 | 0.8482 |
| 0.6677 | 8.0 | 552 | 0.5223 | 0.8554 |
| 0.6206 | 9.0 | 621 | 0.4609 | 0.8732 |
| 0.6543 | 10.0 | 690 | 0.4372 | 0.8679 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.10.1
- Tokenizers 0.13.2