mask2former-finetuned-ER-Mito-LD5
This model is a fine-tuned version of facebook/mask2former-swin-base-IN21k-ade-semantic on the Dnq2025/Mask2former_Pretrain dataset. It achieves the following results on the evaluation set:
- Loss: 33.3884
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: 0.0004
- train_batch_size: 4
- eval_batch_size: 4
- seed: 1337
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: polynomial
- training_steps: 6450
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 53.498 | 1.0 | 129 | 39.6802 |
| 39.3157 | 2.0 | 258 | 35.9394 |
| 37.2096 | 3.0 | 387 | 32.0225 |
| 31.9877 | 4.0 | 516 | 33.2635 |
| 30.1511 | 5.0 | 645 | 29.8756 |
| 28.3667 | 6.0 | 774 | 30.3257 |
| 26.7492 | 7.0 | 903 | 27.9416 |
| 25.6035 | 8.0 | 1032 | 27.4391 |
| 24.5091 | 9.0 | 1161 | 28.4225 |
| 23.8578 | 10.0 | 1290 | 26.4271 |
| 22.6785 | 11.0 | 1419 | 26.4148 |
| 22.0847 | 12.0 | 1548 | 26.6679 |
| 22.0106 | 13.0 | 1677 | 26.7030 |
| 20.45 | 14.0 | 1806 | 26.1600 |
| 20.1949 | 15.0 | 1935 | 26.2444 |
| 19.1922 | 16.0 | 2064 | 27.0105 |
| 18.9458 | 17.0 | 2193 | 24.9449 |
| 18.46 | 18.0 | 2322 | 27.8372 |
| 17.3966 | 19.0 | 2451 | 27.0517 |
| 17.5908 | 20.0 | 2580 | 28.5696 |
| 16.9413 | 21.0 | 2709 | 27.3707 |
| 16.3963 | 22.0 | 2838 | 26.4041 |
| 16.2948 | 23.0 | 2967 | 25.3316 |
| 16.2511 | 24.0 | 3096 | 27.9766 |
| 15.4496 | 25.0 | 3225 | 27.6993 |
| 15.1992 | 26.0 | 3354 | 27.9919 |
| 14.9445 | 27.0 | 3483 | 25.4937 |
| 14.8226 | 28.0 | 3612 | 28.7659 |
| 14.264 | 29.0 | 3741 | 26.7018 |
| 14.348 | 30.0 | 3870 | 28.9018 |
| 13.936 | 31.0 | 3999 | 28.2813 |
| 13.7577 | 32.0 | 4128 | 30.0501 |
| 13.1629 | 33.0 | 4257 | 28.0087 |
| 14.1035 | 34.0 | 4386 | 28.3435 |
| 13.4379 | 35.0 | 4515 | 28.9629 |
| 12.9478 | 36.0 | 4644 | 29.8509 |
| 12.8114 | 37.0 | 4773 | 28.9036 |
| 13.2322 | 38.0 | 4902 | 29.9045 |
| 12.7433 | 39.0 | 5031 | 31.3430 |
| 12.3428 | 40.0 | 5160 | 31.3746 |
| 12.3295 | 41.0 | 5289 | 31.6009 |
| 12.1459 | 42.0 | 5418 | 31.6387 |
| 11.8999 | 43.0 | 5547 | 32.2195 |
| 12.4076 | 44.0 | 5676 | 32.5034 |
| 11.7797 | 45.0 | 5805 | 32.9062 |
| 11.1345 | 46.0 | 5934 | 32.4447 |
| 12.3552 | 47.0 | 6063 | 32.7274 |
| 11.3111 | 48.0 | 6192 | 33.0397 |
| 11.8742 | 49.0 | 6321 | 33.3195 |
| 11.5268 | 50.0 | 6450 | 33.3223 |
Framework versions
- Transformers 4.50.0.dev0
- Pytorch 2.4.1
- Datasets 3.3.2
- Tokenizers 0.21.0
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