metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- image_folder
metrics:
- accuracy
model-index:
- name: resnet-50-4-32
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: image_folder
type: image_folder
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.6409863471719142
resnet-50-4-32
This model is a fine-tuned version of microsoft/resnet-50 on the image_folder dataset. It achieves the following results on the evaluation set:
- Loss: 0.9705
- Accuracy: 0.6410
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: 0.005
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.3833 | 1.0 | 224 | 1.2683 | 0.5134 |
| 1.2404 | 2.0 | 448 | 1.1342 | 0.5659 |
| 1.1492 | 3.0 | 672 | 1.0359 | 0.6087 |
| 1.1433 | 4.0 | 896 | 0.9705 | 0.6410 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1