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: 0.5179628064243449
gemini-beauty
This model is a fine-tuned version of on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.1160
- Accuracy: 0.5180
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 |
|---|---|---|---|---|
| 1.3947 | 1.0 | 148 | 1.2066 | 0.4372 |
| 1.3332 | 2.0 | 296 | 1.1703 | 0.4734 |
| 1.2637 | 3.0 | 444 | 1.1678 | 0.4780 |
| 1.2277 | 4.0 | 592 | 1.1359 | 0.4996 |
| 1.2704 | 5.0 | 740 | 1.1407 | 0.5002 |
| 1.2099 | 6.0 | 888 | 1.1332 | 0.5131 |
| 1.1858 | 7.0 | 1036 | 1.1704 | 0.4803 |
| 1.156 | 8.0 | 1184 | 1.1160 | 0.5180 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0