swinv2-large-patch4-window12to16-192to256-22kto1k-ft-finetuned-galaxy10-decals
This model is a fine-tuned version of microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft on the matthieulel/galaxy10_decals dataset. It achieves the following results on the evaluation set:
- Loss: 0.5226
- Accuracy: 0.8591
- Precision: 0.8571
- Recall: 0.8591
- F1: 0.8567
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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
---|---|---|---|---|---|---|---|
1.0846 | 0.99 | 62 | 0.8092 | 0.7272 | 0.7246 | 0.7272 | 0.7101 |
0.7867 | 2.0 | 125 | 0.6366 | 0.7988 | 0.7996 | 0.7988 | 0.7895 |
0.6835 | 2.99 | 187 | 0.5315 | 0.8207 | 0.8195 | 0.8207 | 0.8157 |
0.586 | 4.0 | 250 | 0.4611 | 0.8489 | 0.8468 | 0.8489 | 0.8452 |
0.5263 | 4.99 | 312 | 0.4753 | 0.8399 | 0.8421 | 0.8399 | 0.8400 |
0.5341 | 6.0 | 375 | 0.4551 | 0.8427 | 0.8433 | 0.8427 | 0.8386 |
0.4743 | 6.99 | 437 | 0.4639 | 0.8382 | 0.8433 | 0.8382 | 0.8391 |
0.4573 | 8.0 | 500 | 0.4771 | 0.8360 | 0.8422 | 0.8360 | 0.8345 |
0.4368 | 8.99 | 562 | 0.4731 | 0.8472 | 0.8450 | 0.8472 | 0.8452 |
0.4022 | 10.0 | 625 | 0.4736 | 0.8540 | 0.8528 | 0.8540 | 0.8516 |
0.4005 | 10.99 | 687 | 0.4542 | 0.8551 | 0.8554 | 0.8551 | 0.8547 |
0.3514 | 12.0 | 750 | 0.5543 | 0.8467 | 0.8527 | 0.8467 | 0.8471 |
0.3565 | 12.99 | 812 | 0.5318 | 0.8506 | 0.8535 | 0.8506 | 0.8493 |
0.3717 | 14.0 | 875 | 0.5059 | 0.8579 | 0.8582 | 0.8579 | 0.8574 |
0.3343 | 14.99 | 937 | 0.5235 | 0.8472 | 0.8492 | 0.8472 | 0.8474 |
0.3053 | 16.0 | 1000 | 0.5226 | 0.8591 | 0.8571 | 0.8591 | 0.8567 |
0.2607 | 16.99 | 1062 | 0.5654 | 0.8591 | 0.8579 | 0.8591 | 0.8572 |
0.2814 | 18.0 | 1125 | 0.5622 | 0.8546 | 0.8541 | 0.8546 | 0.8537 |
0.2735 | 18.99 | 1187 | 0.6185 | 0.8506 | 0.8525 | 0.8506 | 0.8508 |
0.2673 | 20.0 | 1250 | 0.6210 | 0.8574 | 0.8544 | 0.8574 | 0.8550 |
0.2595 | 20.99 | 1312 | 0.6334 | 0.8422 | 0.8415 | 0.8422 | 0.8399 |
0.2583 | 22.0 | 1375 | 0.6565 | 0.8540 | 0.8545 | 0.8540 | 0.8527 |
0.239 | 22.99 | 1437 | 0.6859 | 0.8455 | 0.8458 | 0.8455 | 0.8447 |
0.2174 | 24.0 | 1500 | 0.6709 | 0.8591 | 0.8581 | 0.8591 | 0.8581 |
0.2288 | 24.99 | 1562 | 0.7437 | 0.8444 | 0.8426 | 0.8444 | 0.8419 |
0.2305 | 26.0 | 1625 | 0.7048 | 0.8529 | 0.8497 | 0.8529 | 0.8505 |
0.2071 | 26.99 | 1687 | 0.7152 | 0.8540 | 0.8527 | 0.8540 | 0.8529 |
0.2282 | 28.0 | 1750 | 0.7273 | 0.8568 | 0.8559 | 0.8568 | 0.8554 |
0.209 | 28.99 | 1812 | 0.7213 | 0.8557 | 0.8534 | 0.8557 | 0.8540 |
0.2078 | 29.76 | 1860 | 0.7273 | 0.8563 | 0.8544 | 0.8563 | 0.8548 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.15.1
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