metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: resnet-50-resnet50_fashion
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: 0.8163265306122449
resnet-50-resnet50_fashion
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: 0.7982
- Accuracy: 0.8163
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 7
- total_train_batch_size: 56
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6396 | 0.99 | 86 | 0.7625 | 0.7347 |
| 0.5646 | 2.0 | 173 | 0.5781 | 0.8349 |
| 0.4768 | 2.99 | 259 | 0.4791 | 0.8571 |
| 0.4161 | 4.0 | 346 | 0.3866 | 0.8905 |
| 0.402 | 4.99 | 432 | 0.3294 | 0.9035 |
| 0.369 | 6.0 | 519 | 1.0405 | 0.8924 |
| 0.3512 | 7.0 | 606 | 1.4847 | 0.8905 |
| 0.3439 | 7.99 | 692 | 0.2820 | 0.9054 |
| 0.3306 | 9.0 | 779 | 0.3022 | 0.8850 |
| 0.3691 | 9.93 | 860 | 0.7982 | 0.8163 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3