metadata
library_name: peft
license: apache-2.0
base_model: google/vit-large-patch16-224
tags:
- image-classification
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: vit-large-patch16-224-testing-dungeons-lora-23Nov24-0010
results:
- task:
type: image-classification
name: Image Classification
dataset:
name: rotated_maps
type: imagefolder
config: default
split: validation
args: default
metrics:
- type: accuracy
value: 1
name: Accuracy
vit-large-patch16-224-testing-dungeons-lora-23Nov24-0010
This model is a fine-tuned version of google/vit-large-patch16-224 on the rotated_maps dataset. It achieves the following results on the evaluation set:
- Loss: 0.0977
- Accuracy: 1.0
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: 0.005
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 12
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.6667 | 1 | 1.4309 | 0.2963 |
| No log | 2.0 | 3 | 1.1590 | 0.5926 |
| No log | 2.6667 | 4 | 0.7057 | 0.8148 |
| No log | 4.0 | 6 | 0.4692 | 0.8148 |
| No log | 4.6667 | 7 | 0.2285 | 0.9630 |
| No log | 6.0 | 9 | 0.2492 | 0.8889 |
| 0.7456 | 6.6667 | 10 | 0.1295 | 1.0 |
| 0.7456 | 8.0 | 12 | 0.0977 | 1.0 |
Framework versions
- PEFT 0.13.2
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3