Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use lngrid2020/vit-part1-friends with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lngrid2020/vit-part1-friends with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="lngrid2020/vit-part1-friends") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("lngrid2020/vit-part1-friends") model = AutoModelForImageClassification.from_pretrained("lngrid2020/vit-part1-friends", device_map="auto") - Notebooks
- Google Colab
- Kaggle
vit-part1-friends
This model is a fine-tuned version of moreover18/vit-base-patch16-224-in21k-YB on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.2036
- Accuracy: 0.9381
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 7
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.1627 | 1.3 | 50 | 0.2258 | 0.9202 |
| 0.1183 | 2.6 | 100 | 0.2148 | 0.9235 |
| 0.1223 | 3.9 | 150 | 0.2055 | 0.9267 |
| 0.0992 | 5.19 | 200 | 0.1976 | 0.9332 |
| 0.0824 | 6.49 | 250 | 0.2036 | 0.9381 |
Framework versions
- Transformers 4.37.1
- Pytorch 1.12.1+cu116
- Datasets 2.4.0
- Tokenizers 0.15.1
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Model tree for lngrid2020/vit-part1-friends
Evaluation results
- Accuracy on imagefolderself-reported0.938