metadata
base_model: google/vit-base-patch16-224-in21k
datasets:
- imagefolder
library_name: peft
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: vit-base-patch16-224-in21k-finetuned-qlora-houseplant
results: []
vit-base-patch16-224-in21k-finetuned-qlora-houseplant
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.6871
- Accuracy: 0.5306
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: 1e-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: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 7 | 0.6917 | 0.5 |
| 0.688 | 2.0 | 14 | 0.6908 | 0.5204 |
| 0.6843 | 3.0 | 21 | 0.6899 | 0.5204 |
| 0.6843 | 4.0 | 28 | 0.6892 | 0.5204 |
| 0.6871 | 5.0 | 35 | 0.6886 | 0.5204 |
| 0.6833 | 6.0 | 42 | 0.6880 | 0.5204 |
| 0.6833 | 7.0 | 49 | 0.6876 | 0.5204 |
| 0.6812 | 8.0 | 56 | 0.6873 | 0.5204 |
| 0.6807 | 9.0 | 63 | 0.6871 | 0.5306 |
| 0.6829 | 10.0 | 70 | 0.6870 | 0.5306 |
Framework versions
- PEFT 0.12.1.dev0
- Transformers 4.45.0.dev0
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1