|
--- |
|
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 |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# gemini-beauty |
|
|
|
This model is a fine-tuned version of [](https://huggingface.co/) 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 |
|
|
