Hugging Face's logo

al-css
/
faces_classification

Image Classification
Transformers
Safetensors
vit
image-classification, faces-recognition
Generated from Trainer
Inference Endpoints
Model card Files Community
faces_classification / README.md
al-css's picture
al-css
Modelo de reconocimiento de rostros
49e2c91 verified
preview code
|
raw
history blame contribute delete
8.12 kB
metadata
library_name: transformers
base_model: lokeshk/Face-Recognition-NM
tags:
  - image-classification, faces-recognition
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: faces_clasification_alcss
    results: []

faces_clasification_alcss

This model is a fine-tuned version of lokeshk/Face-Recognition-NM on the private_faces_dataset dataset. It achieves the following results on the evaluation set:

  • Loss: 2.2189
  • Accuracy: 0.5481

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: 0.0001
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy
4.6929 0.0962 10 4.5349 0.0913
4.4502 0.1923 20 4.3568 0.1010
4.3178 0.2885 30 4.2414 0.0865
4.2083 0.3846 40 4.1396 0.1731
4.1225 0.4808 50 4.0550 0.1538
3.908 0.5769 60 3.9737 0.1683
3.9502 0.6731 70 3.9053 0.1683
3.8725 0.7692 80 3.8432 0.1731
3.7944 0.8654 90 3.7840 0.2115
3.7648 0.9615 100 3.7644 0.1971
3.7211 1.0577 110 3.7172 0.1971
3.5759 1.1538 120 3.6622 0.25
3.6082 1.25 130 3.6080 0.2644
3.4272 1.3462 140 3.5738 0.2837
3.3349 1.4423 150 3.5526 0.2740
3.189 1.5385 160 3.5162 0.2837
3.2959 1.6346 170 3.4639 0.2933
3.1273 1.7308 180 3.4308 0.3365
3.1621 1.8269 190 3.3436 0.3221
3.1053 1.9231 200 3.2973 0.3702
3.0641 2.0192 210 3.2637 0.3462
2.6593 2.1154 220 3.2149 0.3798
2.5709 2.2115 230 3.1658 0.3846
2.5412 2.3077 240 3.1359 0.3702
2.5775 2.4038 250 3.1104 0.3654
2.6372 2.5 260 3.1027 0.3798
2.6732 2.5962 270 3.0252 0.4231
2.6384 2.6923 280 3.0202 0.3942
2.4607 2.7885 290 2.9785 0.4135
2.5519 2.8846 300 2.9470 0.4327
2.2381 2.9808 310 2.9402 0.4231
2.1999 3.0769 320 2.9074 0.4519
2.179 3.1731 330 2.8780 0.4567
2.1427 3.2692 340 2.8331 0.4423
2.1335 3.3654 350 2.8051 0.4760
1.7641 3.4615 360 2.7798 0.4712
1.9687 3.5577 370 2.7607 0.4808
1.8046 3.6538 380 2.7381 0.4760
1.944 3.75 390 2.7244 0.4856
1.7403 3.8462 400 2.6899 0.4567
1.7732 3.9423 410 2.6656 0.4808
1.4105 4.0385 420 2.6526 0.4760
1.377 4.1346 430 2.6448 0.4904
1.5767 4.2308 440 2.5933 0.4663
1.3826 4.3269 450 2.5832 0.5
1.6504 4.4231 460 2.5573 0.5192
1.5579 4.5192 470 2.5666 0.5048
1.2466 4.6154 480 2.5197 0.5144
1.32 4.7115 490 2.5145 0.5240
1.5286 4.8077 500 2.4909 0.5192
1.394 4.9038 510 2.4882 0.5192
1.3982 5.0 520 2.4616 0.5192
1.1167 5.0962 530 2.4569 0.5096
1.3562 5.1923 540 2.4559 0.5192
1.0018 5.2885 550 2.4438 0.5192
1.2367 5.3846 560 2.4204 0.5192
1.1748 5.4808 570 2.4112 0.5337
1.022 5.5769 580 2.4130 0.5385
1.0954 5.6731 590 2.3992 0.5192
0.9759 5.7692 600 2.3683 0.5240
1.0327 5.8654 610 2.3577 0.5144
1.1167 5.9615 620 2.3547 0.5144
0.8077 6.0577 630 2.3452 0.5385
0.95 6.1538 640 2.3486 0.5433
0.7993 6.25 650 2.3428 0.5529
0.923 6.3462 660 2.3279 0.5337
0.7566 6.4423 670 2.3176 0.5385
0.8834 6.5385 680 2.3201 0.5288
0.9337 6.6346 690 2.3064 0.5529
0.7596 6.7308 700 2.3063 0.5288
0.973 6.8269 710 2.2847 0.5337
1.0212 6.9231 720 2.3006 0.5433
0.8315 7.0192 730 2.2813 0.5385
0.814 7.1154 740 2.2751 0.5481
0.7658 7.2115 750 2.2754 0.5433
0.5956 7.3077 760 2.2781 0.5433
0.8864 7.4038 770 2.2602 0.5529
0.7181 7.5 780 2.2568 0.5721
0.643 7.5962 790 2.2586 0.5481
0.7107 7.6923 800 2.2520 0.5337
0.6078 7.7885 810 2.2423 0.5385
0.873 7.8846 820 2.2478 0.5337
0.7018 7.9808 830 2.2357 0.5577
0.7177 8.0769 840 2.2340 0.5481
0.6543 8.1731 850 2.2337 0.5481
0.7563 8.2692 860 2.2259 0.5529
0.549 8.3654 870 2.2310 0.5529
0.6981 8.4615 880 2.2381 0.5529
0.6172 8.5577 890 2.2285 0.5481
0.587 8.6538 900 2.2165 0.5481
0.613 8.75 910 2.2215 0.5481
0.5558 8.8462 920 2.2274 0.5529
0.6892 8.9423 930 2.2221 0.5433
0.5876 9.0385 940 2.2209 0.5481
0.5845 9.1346 950 2.2211 0.5481
0.645 9.2308 960 2.2208 0.5481
0.5619 9.3269 970 2.2204 0.5481
0.5371 9.4231 980 2.2219 0.5481
0.5048 9.5192 990 2.2203 0.5481
0.6007 9.6154 1000 2.2192 0.5481
0.5706 9.7115 1010 2.2187 0.5481
0.571 9.8077 1020 2.2189 0.5481
0.6692 9.9038 1030 2.2191 0.5481
0.5411 10.0 1040 2.2189 0.5481

Framework versions

  • Transformers 4.44.1
  • Pytorch 2.4.0+cu118
  • Datasets 2.21.0
  • Tokenizers 0.19.1