metadata
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: gemini-beauty
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: 0.5158495350803043
gemini-beauty
This model is a fine-tuned version of on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.1226
- Accuracy: 0.5158
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: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.3724 | 1.0 | 148 | 1.2028 | 0.4586 |
| 1.3217 | 2.0 | 296 | 1.1831 | 0.4812 |
| 1.2649 | 3.0 | 444 | 1.1674 | 0.4981 |
| 1.2456 | 4.0 | 592 | 1.1236 | 0.5146 |
| 1.2176 | 5.0 | 740 | 1.1384 | 0.5040 |
| 1.2069 | 6.0 | 888 | 1.1165 | 0.5207 |
| 1.2083 | 7.0 | 1036 | 1.1663 | 0.4985 |
| 1.1663 | 8.0 | 1184 | 1.1226 | 0.5158 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0