metadata
tags:
- generated_from_trainer
datasets:
- preprocessed1024_config
metrics:
- accuracy
- f1
model-index:
- name: convnext-mlo-512-breat_composition-ordinal
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: preprocessed1024_config
type: preprocessed1024_config
args: default
metrics:
- name: Accuracy
type: accuracy
value:
accuracy: 1
- name: F1
type: f1
value:
f1: 1
convnext-mlo-512-breat_composition-ordinal
This model is a fine-tuned version of on the preprocessed1024_config dataset. It achieves the following results on the evaluation set:
- Loss: 0.0250
- Accuracy: {'accuracy': 1.0}
- F1: {'f1': 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.0899 | 1.0 | 796 | 0.0727 | {'accuracy': 1.0} | {'f1': 1.0} |
| 0.0451 | 2.0 | 1592 | 0.0395 | {'accuracy': 1.0} | {'f1': 1.0} |
| 0.0388 | 3.0 | 2388 | 0.0382 | {'accuracy': 1.0} | {'f1': 1.0} |
| 0.0298 | 4.0 | 3184 | 0.0310 | {'accuracy': 1.0} | {'f1': 1.0} |
| 0.0239 | 5.0 | 3980 | 0.0394 | {'accuracy': 1.0} | {'f1': 1.0} |
| 0.0194 | 6.0 | 4776 | 0.0254 | {'accuracy': 1.0} | {'f1': 1.0} |
| 0.0178 | 7.0 | 5572 | 0.0248 | {'accuracy': 1.0} | {'f1': 1.0} |
| 0.0155 | 8.0 | 6368 | 0.0258 | {'accuracy': 1.0} | {'f1': 1.0} |
| 0.0137 | 9.0 | 7164 | 0.0247 | {'accuracy': 1.0} | {'f1': 1.0} |
| 0.0129 | 10.0 | 7960 | 0.0250 | {'accuracy': 1.0} | {'f1': 1.0} |
Framework versions
- Transformers 4.20.1
- Pytorch 1.12.0
- Datasets 2.1.0
- Tokenizers 0.12.1