metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: resnet-50-finetuned-omars5
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: 0.8844984802431611
resnet-50-finetuned-omars5
This model is a fine-tuned version of microsoft/resnet-50 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.5844
- Accuracy: 0.8845
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: 0.0005
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.3431 | 0.99 | 92 | 1.2810 | 0.5836 |
| 1.0465 | 2.0 | 185 | 0.8740 | 0.8176 |
| 0.8755 | 2.99 | 277 | 0.6467 | 0.7994 |
| 0.7459 | 4.0 | 370 | 0.5379 | 0.8480 |
| 0.7983 | 4.99 | 462 | 0.4385 | 0.8207 |
| 0.7692 | 6.0 | 555 | 0.5795 | 0.7842 |
| 0.5158 | 6.99 | 647 | 0.4936 | 0.8207 |
| 0.625 | 8.0 | 740 | 0.5316 | 0.8298 |
| 0.511 | 8.99 | 832 | 0.5202 | 0.8845 |
| 0.5025 | 10.0 | 925 | 0.5260 | 0.8784 |
| 0.508 | 10.99 | 1017 | 0.5307 | 0.8632 |
| 0.4652 | 12.0 | 1110 | 0.6060 | 0.8480 |
| 0.4432 | 12.99 | 1202 | 0.5051 | 0.8845 |
| 0.3373 | 14.0 | 1295 | 0.8695 | 0.8845 |
| 0.3968 | 14.99 | 1387 | 0.6805 | 0.8571 |
| 0.4268 | 16.0 | 1480 | 0.6541 | 0.8815 |
| 0.3029 | 16.99 | 1572 | 0.5710 | 0.8906 |
| 0.3801 | 18.0 | 1665 | 0.6499 | 0.8571 |
| 0.3545 | 18.99 | 1757 | 0.6727 | 0.8419 |
| 0.3526 | 20.0 | 1850 | 0.6542 | 0.8571 |
| 0.3458 | 20.99 | 1942 | 0.6625 | 0.8997 |
| 0.3078 | 22.0 | 2035 | 0.6551 | 0.8784 |
| 0.3677 | 22.99 | 2127 | 0.5953 | 0.8815 |
| 0.3386 | 24.0 | 2220 | 0.6549 | 0.8693 |
| 0.213 | 24.99 | 2312 | 0.5846 | 0.8997 |
| 0.3778 | 26.0 | 2405 | 0.6746 | 0.8602 |
| 0.3079 | 26.99 | 2497 | 0.6594 | 0.8997 |
| 0.2943 | 28.0 | 2590 | 0.6246 | 0.8815 |
| 0.2782 | 28.99 | 2682 | 0.6550 | 0.8906 |
| 0.2931 | 29.84 | 2760 | 0.5844 | 0.8845 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu117
- Datasets 2.13.0
- Tokenizers 0.13.3