UL_bedroom_classification
This model is a fine-tuned version of google/vit-base-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.1283
- Accuracy: 0.9578
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: 7
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 0.9730 | 9 | 0.4275 | 0.8464 |
0.7101 | 1.9459 | 18 | 0.1990 | 0.9518 |
0.3133 | 2.9189 | 27 | 0.1399 | 0.9548 |
0.2012 | 4.0 | 37 | 0.1229 | 0.9548 |
0.1724 | 4.9730 | 46 | 0.1384 | 0.9488 |
0.1458 | 5.9459 | 55 | 0.1240 | 0.9518 |
0.1476 | 6.8108 | 63 | 0.1283 | 0.9578 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Base model
google/vit-base-patch16-224Evaluation results
- Accuracy on imagefoldervalidation set self-reported0.958