metadata
license: other
base_model: google/mobilenet_v2_1.4_224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: MobileNet-V2-Retinopathy
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9306930693069307
MobileNet-V2-Retinopathy
This model is a fine-tuned version of google/mobilenet_v2_1.4_224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.2044
- Accuracy: 0.9307
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.4403 | 1.0 | 113 | 0.5330 | 0.7079 |
| 0.5538 | 2.0 | 227 | 0.4312 | 0.7723 |
| 0.542 | 3.0 | 340 | 0.5137 | 0.7426 |
| 0.4776 | 4.0 | 454 | 0.4656 | 0.7723 |
| 0.4244 | 5.0 | 567 | 1.0400 | 0.5990 |
| 0.4694 | 6.0 | 681 | 0.5936 | 0.7228 |
| 0.4494 | 7.0 | 794 | 0.4667 | 0.7822 |
| 0.4647 | 8.0 | 908 | 0.2629 | 0.8960 |
| 0.3646 | 9.0 | 1021 | 0.2287 | 0.8861 |
| 0.4827 | 10.0 | 1135 | 1.7967 | 0.5149 |
| 0.3679 | 11.0 | 1248 | 0.4184 | 0.8267 |
| 0.3454 | 12.0 | 1362 | 0.1885 | 0.9406 |
| 0.3562 | 13.0 | 1475 | 0.2798 | 0.9059 |
| 0.3397 | 14.0 | 1589 | 1.6444 | 0.5891 |
| 0.4047 | 14.93 | 1695 | 0.2044 | 0.9307 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1