metadata
license: apache-2.0
base_model: microsoft/resnet-18
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: resnet-18
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: 1
resnet-18
This model is a fine-tuned version of microsoft/resnet-18 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.7117
- Accuracy: 1.0
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: 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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.9091 | 5 | 1.0318 | 0.4156 |
| 1.0893 | 2.0 | 11 | 0.9520 | 0.6364 |
| 1.0893 | 2.9091 | 16 | 0.9017 | 0.8442 |
| 0.9912 | 4.0 | 22 | 0.8444 | 1.0 |
| 0.9912 | 4.9091 | 27 | 0.8027 | 1.0 |
| 0.9248 | 6.0 | 33 | 0.7631 | 1.0 |
| 0.9248 | 6.9091 | 38 | 0.7369 | 1.0 |
| 0.8716 | 8.0 | 44 | 0.7156 | 1.0 |
| 0.8716 | 8.9091 | 49 | 0.7137 | 1.0 |
| 0.8517 | 9.0909 | 50 | 0.7117 | 1.0 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1