metadata
license: apache-2.0
base_model: facebook/dinov2-base-imagenet1k-1-layer
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
- matthews_correlation
model-index:
- name: dinov2-base-imagenet1k-1-layer-boulderspot-vN
results: []
dinov2-base-imagenet1k-1-layer-boulderspot-vN
This model is a fine-tuned version of facebook/dinov2-base-imagenet1k-1-layer on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0519
- Accuracy: 0.9810
- F1: 0.9809
- Precision: 0.9808
- Recall: 0.9810
- Matthews Correlation: 0.8501
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 7395
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 5.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Matthews Correlation |
|---|---|---|---|---|---|---|---|---|
| 0.1596 | 1.0 | 203 | 0.0733 | 0.9766 | 0.9759 | 0.9757 | 0.9766 | 0.8079 |
| 0.0635 | 2.0 | 406 | 0.1276 | 0.9474 | 0.9522 | 0.9619 | 0.9474 | 0.6845 |
| 0.1031 | 3.0 | 609 | 0.0602 | 0.9751 | 0.9755 | 0.9760 | 0.9751 | 0.8118 |
| 0.0587 | 4.0 | 813 | 0.0512 | 0.9737 | 0.9734 | 0.9732 | 0.9737 | 0.7905 |
| 0.038 | 4.99 | 1015 | 0.0519 | 0.9810 | 0.9809 | 0.9808 | 0.9810 | 0.8501 |
Framework versions
- Transformers 4.39.2
- Pytorch 2.4.0.dev20240328+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2