File size: 2,423 Bytes
238558d f80e06c 238558d 2a66bc7 238558d f80e06c 238558d 2a66bc7 238558d f80e06c 238558d 2a66bc7 238558d f80e06c 238558d f80e06c |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 |
---
library_name: peft
license: apache-2.0
base_model: facebook/dinov2-small
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- recall
- precision
model-index:
- name: dinov2_LoRA_Liveness_detection_v1.0
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/nguyenkhoaht002/liveness_detection/runs/qt5odc7e)
# dinov2_LoRA_Liveness_detection_v1.0
This model is a fine-tuned version of [facebook/dinov2-small](https://huggingface.co/facebook/dinov2-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0073
- Accuracy: 0.9979
- F1: 0.9979
- Recall: 0.9979
- Precision: 0.9979
## 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: 512
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
| 0.0256 | 0.4076 | 64 | 0.0211 | 0.9931 | 0.9931 | 0.9931 | 0.9931 |
| 0.0164 | 0.8153 | 128 | 0.0153 | 0.9943 | 0.9943 | 0.9943 | 0.9943 |
| 0.0073 | 1.2229 | 192 | 0.0116 | 0.9962 | 0.9962 | 0.9962 | 0.9962 |
| 0.0073 | 1.6306 | 256 | 0.0073 | 0.9974 | 0.9974 | 0.9974 | 0.9974 |
| 0.0082 | 2.0382 | 320 | 0.0076 | 0.9977 | 0.9977 | 0.9977 | 0.9977 |
| 0.0048 | 2.4459 | 384 | 0.0070 | 0.9977 | 0.9977 | 0.9977 | 0.9977 |
| 0.0019 | 2.8535 | 448 | 0.0073 | 0.9979 | 0.9979 | 0.9979 | 0.9979 |
### Framework versions
- PEFT 0.14.0
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1 |