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---
library_name: peft
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
datasets:
- biobert_json
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: xml-roberta-large-16size
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. -->
# xml-roberta-large-16size
This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the biobert_json dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0772
- Precision: 0.9394
- Recall: 0.9575
- F1: 0.9484
- Accuracy: 0.9814
## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use paged_adamw_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- training_steps: 3055
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0586 | 0.0327 | 20 | 0.0947 | 0.9408 | 0.9376 | 0.9392 | 0.9777 |
| 0.0957 | 0.0654 | 40 | 0.1089 | 0.9094 | 0.9434 | 0.9261 | 0.9715 |
| 0.077 | 0.0980 | 60 | 0.0997 | 0.9080 | 0.9434 | 0.9253 | 0.9729 |
| 0.0833 | 0.1307 | 80 | 0.0997 | 0.9148 | 0.9405 | 0.9275 | 0.9747 |
| 0.133 | 0.1634 | 100 | 0.1056 | 0.9167 | 0.9323 | 0.9244 | 0.9721 |
| 0.1114 | 0.1961 | 120 | 0.1093 | 0.9034 | 0.9351 | 0.9190 | 0.9710 |
| 0.0885 | 0.2288 | 140 | 0.0952 | 0.9266 | 0.9406 | 0.9335 | 0.9771 |
| 0.0822 | 0.2614 | 160 | 0.1081 | 0.9107 | 0.9410 | 0.9256 | 0.9730 |
| 0.0839 | 0.2941 | 180 | 0.0946 | 0.9157 | 0.9567 | 0.9357 | 0.9755 |
| 0.0829 | 0.3268 | 200 | 0.1040 | 0.8927 | 0.9509 | 0.9209 | 0.9713 |
| 0.0925 | 0.3595 | 220 | 0.0975 | 0.9004 | 0.9515 | 0.9253 | 0.9735 |
| 0.1239 | 0.3922 | 240 | 0.1035 | 0.8965 | 0.9485 | 0.9218 | 0.9727 |
| 0.0817 | 0.4248 | 260 | 0.0891 | 0.9211 | 0.9493 | 0.9350 | 0.9761 |
| 0.0772 | 0.4575 | 280 | 0.0879 | 0.9189 | 0.9512 | 0.9348 | 0.9762 |
| 0.0817 | 0.4902 | 300 | 0.0786 | 0.9345 | 0.9490 | 0.9417 | 0.9793 |
| 0.0849 | 0.5229 | 320 | 0.0925 | 0.9160 | 0.9277 | 0.9218 | 0.9735 |
| 0.1045 | 0.5556 | 340 | 0.0985 | 0.8888 | 0.9336 | 0.9106 | 0.9708 |
| 0.0932 | 0.5882 | 360 | 0.0844 | 0.9178 | 0.9576 | 0.9373 | 0.9771 |
| 0.0844 | 0.6209 | 380 | 0.0819 | 0.9217 | 0.9627 | 0.9417 | 0.9776 |
| 0.0768 | 0.6536 | 400 | 0.0960 | 0.9089 | 0.9593 | 0.9334 | 0.9742 |
| 0.0723 | 0.6863 | 420 | 0.0877 | 0.9148 | 0.9534 | 0.9337 | 0.9755 |
| 0.0817 | 0.7190 | 440 | 0.0906 | 0.9159 | 0.9445 | 0.9299 | 0.9743 |
| 0.085 | 0.7516 | 460 | 0.0780 | 0.9138 | 0.9406 | 0.9270 | 0.9761 |
| 0.0911 | 0.7843 | 480 | 0.0862 | 0.9279 | 0.9569 | 0.9422 | 0.9777 |
| 0.0818 | 0.8170 | 500 | 0.0796 | 0.9309 | 0.9464 | 0.9386 | 0.9779 |
| 0.0568 | 0.8497 | 520 | 0.0908 | 0.9192 | 0.9484 | 0.9336 | 0.9763 |
| 0.0763 | 0.8824 | 540 | 0.0901 | 0.9181 | 0.9545 | 0.9360 | 0.9766 |
| 0.0874 | 0.9150 | 560 | 0.0956 | 0.9084 | 0.9509 | 0.9292 | 0.9742 |
| 0.0809 | 0.9477 | 580 | 0.0929 | 0.9020 | 0.9586 | 0.9294 | 0.9741 |
| 0.094 | 0.9804 | 600 | 0.0777 | 0.9339 | 0.9491 | 0.9415 | 0.9793 |
| 0.0913 | 1.0131 | 620 | 0.0937 | 0.9090 | 0.9482 | 0.9282 | 0.9724 |
| 0.0488 | 1.0458 | 640 | 0.1043 | 0.8994 | 0.9445 | 0.9214 | 0.9724 |
| 0.0627 | 1.0784 | 660 | 0.0789 | 0.9312 | 0.9581 | 0.9445 | 0.9801 |
| 0.0573 | 1.1111 | 680 | 0.0927 | 0.9149 | 0.9577 | 0.9359 | 0.9759 |
| 0.0643 | 1.1438 | 700 | 0.0870 | 0.9192 | 0.9599 | 0.9391 | 0.9772 |
| 0.0784 | 1.1765 | 720 | 0.0788 | 0.9334 | 0.9567 | 0.9449 | 0.9796 |
| 0.0656 | 1.2092 | 740 | 0.0869 | 0.9313 | 0.9424 | 0.9368 | 0.9776 |
| 0.0814 | 1.2418 | 760 | 0.0841 | 0.9296 | 0.9552 | 0.9423 | 0.9787 |
| 0.0878 | 1.2745 | 780 | 0.0831 | 0.9214 | 0.9507 | 0.9358 | 0.9776 |
| 0.0755 | 1.3072 | 800 | 0.0890 | 0.9314 | 0.9494 | 0.9403 | 0.9781 |
| 0.0751 | 1.3399 | 820 | 0.0881 | 0.9183 | 0.9342 | 0.9262 | 0.9750 |
| 0.0599 | 1.3725 | 840 | 0.0848 | 0.9262 | 0.9318 | 0.9290 | 0.9749 |
| 0.0653 | 1.4052 | 860 | 0.0826 | 0.9243 | 0.9556 | 0.9397 | 0.9785 |
| 0.0683 | 1.4379 | 880 | 0.0861 | 0.9239 | 0.9459 | 0.9348 | 0.9774 |
| 0.0811 | 1.4706 | 900 | 0.0847 | 0.9113 | 0.9539 | 0.9321 | 0.9751 |
| 0.0583 | 1.5033 | 920 | 0.0790 | 0.9273 | 0.9500 | 0.9385 | 0.9771 |
| 0.0483 | 1.5359 | 940 | 0.0779 | 0.9296 | 0.9501 | 0.9397 | 0.9792 |
| 0.0828 | 1.5686 | 960 | 0.0812 | 0.9274 | 0.9537 | 0.9403 | 0.9775 |
| 0.0652 | 1.6013 | 980 | 0.0847 | 0.9190 | 0.9393 | 0.9290 | 0.9775 |
| 0.0619 | 1.6340 | 1000 | 0.0989 | 0.9171 | 0.9455 | 0.9311 | 0.9746 |
| 0.0558 | 1.6667 | 1020 | 0.0837 | 0.9276 | 0.9581 | 0.9426 | 0.9782 |
| 0.0564 | 1.6993 | 1040 | 0.0905 | 0.9148 | 0.9569 | 0.9354 | 0.9761 |
| 0.0473 | 1.7320 | 1060 | 0.0818 | 0.9339 | 0.9561 | 0.9449 | 0.9795 |
| 0.0622 | 1.7647 | 1080 | 0.0898 | 0.9074 | 0.9382 | 0.9226 | 0.9753 |
| 0.0589 | 1.7974 | 1100 | 0.0799 | 0.9375 | 0.9483 | 0.9429 | 0.9800 |
| 0.078 | 1.8301 | 1120 | 0.0824 | 0.9271 | 0.9550 | 0.9409 | 0.9773 |
| 0.0624 | 1.8627 | 1140 | 0.0761 | 0.9388 | 0.9487 | 0.9437 | 0.9801 |
| 0.0656 | 1.8954 | 1160 | 0.0833 | 0.9191 | 0.9425 | 0.9307 | 0.9763 |
| 0.0608 | 1.9281 | 1180 | 0.0851 | 0.9315 | 0.9587 | 0.9449 | 0.9795 |
| 0.0697 | 1.9608 | 1200 | 0.0916 | 0.9233 | 0.9539 | 0.9384 | 0.9764 |
| 0.0676 | 1.9935 | 1220 | 0.0794 | 0.9247 | 0.9537 | 0.9390 | 0.9790 |
| 0.0488 | 2.0261 | 1240 | 0.0738 | 0.938 | 0.9543 | 0.9461 | 0.9811 |
| 0.09 | 2.0588 | 1260 | 0.0799 | 0.9388 | 0.9489 | 0.9438 | 0.9804 |
| 0.0518 | 2.0915 | 1280 | 0.0782 | 0.9358 | 0.9585 | 0.9470 | 0.9807 |
| 0.0359 | 2.1242 | 1300 | 0.0769 | 0.9328 | 0.9556 | 0.9441 | 0.9805 |
| 0.0379 | 2.1569 | 1320 | 0.0829 | 0.9397 | 0.9502 | 0.9450 | 0.9804 |
| 0.0766 | 2.1895 | 1340 | 0.0875 | 0.9118 | 0.9460 | 0.9286 | 0.9759 |
| 0.0458 | 2.2222 | 1360 | 0.0856 | 0.9244 | 0.9588 | 0.9413 | 0.9780 |
| 0.0469 | 2.2549 | 1380 | 0.0945 | 0.9167 | 0.9557 | 0.9358 | 0.9752 |
| 0.0565 | 2.2876 | 1400 | 0.0886 | 0.9318 | 0.9417 | 0.9367 | 0.9768 |
| 0.0636 | 2.3203 | 1420 | 0.0810 | 0.9357 | 0.9543 | 0.9449 | 0.9801 |
| 0.044 | 2.3529 | 1440 | 0.0803 | 0.9375 | 0.9502 | 0.9438 | 0.9807 |
| 0.0576 | 2.3856 | 1460 | 0.0776 | 0.9373 | 0.9569 | 0.9470 | 0.9808 |
| 0.0471 | 2.4183 | 1480 | 0.0804 | 0.9323 | 0.9473 | 0.9397 | 0.9791 |
| 0.0727 | 2.4510 | 1500 | 0.0987 | 0.8974 | 0.9471 | 0.9216 | 0.9737 |
| 0.0577 | 2.4837 | 1520 | 0.0779 | 0.9396 | 0.9567 | 0.9480 | 0.9809 |
| 0.0459 | 2.5163 | 1540 | 0.0809 | 0.9398 | 0.9549 | 0.9473 | 0.9810 |
| 0.0498 | 2.5490 | 1560 | 0.0851 | 0.9311 | 0.9540 | 0.9424 | 0.9795 |
| 0.0629 | 2.5817 | 1580 | 0.0788 | 0.9351 | 0.9533 | 0.9441 | 0.9802 |
| 0.071 | 2.6144 | 1600 | 0.0827 | 0.9289 | 0.9582 | 0.9433 | 0.9786 |
| 0.058 | 2.6471 | 1620 | 0.0939 | 0.9219 | 0.9579 | 0.9395 | 0.9760 |
| 0.0532 | 2.6797 | 1640 | 0.0771 | 0.9331 | 0.9580 | 0.9454 | 0.9793 |
| 0.0456 | 2.7124 | 1660 | 0.0783 | 0.9414 | 0.9536 | 0.9474 | 0.9809 |
| 0.0577 | 2.7451 | 1680 | 0.1302 | 0.9182 | 0.9138 | 0.9160 | 0.9714 |
| 0.0559 | 2.7778 | 1700 | 0.0848 | 0.9273 | 0.9556 | 0.9412 | 0.9786 |
| 0.0561 | 2.8105 | 1720 | 0.0865 | 0.9290 | 0.9546 | 0.9416 | 0.9784 |
| 0.0688 | 2.8431 | 1740 | 0.0819 | 0.9247 | 0.9555 | 0.9398 | 0.9776 |
| 0.0429 | 2.8758 | 1760 | 0.0830 | 0.9279 | 0.9534 | 0.9405 | 0.9787 |
| 0.0445 | 2.9085 | 1780 | 0.0808 | 0.9372 | 0.9515 | 0.9443 | 0.9798 |
| 0.0599 | 2.9412 | 1800 | 0.0855 | 0.9225 | 0.9573 | 0.9396 | 0.9781 |
| 0.057 | 2.9739 | 1820 | 0.0794 | 0.9336 | 0.9582 | 0.9458 | 0.9804 |
| 0.0408 | 3.0065 | 1840 | 0.0794 | 0.9312 | 0.9597 | 0.9452 | 0.9808 |
| 0.0423 | 3.0392 | 1860 | 0.0827 | 0.9282 | 0.9509 | 0.9394 | 0.9792 |
| 0.0284 | 3.0719 | 1880 | 0.0798 | 0.9340 | 0.9570 | 0.9454 | 0.9807 |
| 0.0354 | 3.1046 | 1900 | 0.0795 | 0.9332 | 0.9575 | 0.9452 | 0.9800 |
| 0.0384 | 3.1373 | 1920 | 0.0800 | 0.9338 | 0.9593 | 0.9464 | 0.9799 |
| 0.0433 | 3.1699 | 1940 | 0.0801 | 0.9309 | 0.9593 | 0.9449 | 0.9796 |
| 0.0332 | 3.2026 | 1960 | 0.0780 | 0.9353 | 0.9502 | 0.9427 | 0.9796 |
| 0.0362 | 3.2353 | 1980 | 0.0852 | 0.9214 | 0.9568 | 0.9388 | 0.9778 |
| 0.0388 | 3.2680 | 2000 | 0.0774 | 0.9353 | 0.9562 | 0.9456 | 0.9804 |
| 0.0301 | 3.3007 | 2020 | 0.0799 | 0.9342 | 0.9560 | 0.9449 | 0.9804 |
| 0.0497 | 3.3333 | 2040 | 0.0801 | 0.9325 | 0.9481 | 0.9402 | 0.9796 |
| 0.0416 | 3.3660 | 2060 | 0.0739 | 0.9420 | 0.9557 | 0.9488 | 0.9813 |
| 0.044 | 3.3987 | 2080 | 0.0845 | 0.9193 | 0.9574 | 0.9380 | 0.9781 |
| 0.0364 | 3.4314 | 2100 | 0.0723 | 0.9395 | 0.9508 | 0.9451 | 0.9808 |
| 0.0482 | 3.4641 | 2120 | 0.0884 | 0.9175 | 0.9472 | 0.9321 | 0.9761 |
| 0.0344 | 3.4967 | 2140 | 0.0762 | 0.9418 | 0.9542 | 0.9479 | 0.9812 |
| 0.035 | 3.5294 | 2160 | 0.0907 | 0.9106 | 0.9458 | 0.9278 | 0.9753 |
| 0.0406 | 3.5621 | 2180 | 0.0775 | 0.9340 | 0.9495 | 0.9417 | 0.9794 |
| 0.0385 | 3.5948 | 2200 | 0.0817 | 0.9341 | 0.9564 | 0.9451 | 0.9798 |
| 0.0289 | 3.6275 | 2220 | 0.0774 | 0.9409 | 0.9598 | 0.9502 | 0.9817 |
| 0.027 | 3.6601 | 2240 | 0.0772 | 0.9374 | 0.9548 | 0.9460 | 0.9808 |
| 0.0438 | 3.6928 | 2260 | 0.0817 | 0.9312 | 0.9543 | 0.9426 | 0.9793 |
| 0.0396 | 3.7255 | 2280 | 0.0805 | 0.9366 | 0.9567 | 0.9465 | 0.9801 |
| 0.0462 | 3.7582 | 2300 | 0.0792 | 0.9345 | 0.9591 | 0.9466 | 0.9804 |
| 0.0312 | 3.7908 | 2320 | 0.0750 | 0.9391 | 0.9574 | 0.9481 | 0.9810 |
| 0.0454 | 3.8235 | 2340 | 0.0786 | 0.9311 | 0.9588 | 0.9447 | 0.9798 |
| 0.0421 | 3.8562 | 2360 | 0.0776 | 0.9368 | 0.9551 | 0.9459 | 0.9802 |
| 0.0399 | 3.8889 | 2380 | 0.0839 | 0.9287 | 0.9588 | 0.9435 | 0.9785 |
| 0.053 | 3.9216 | 2400 | 0.0820 | 0.9302 | 0.9564 | 0.9431 | 0.9787 |
| 0.0415 | 3.9542 | 2420 | 0.0763 | 0.9412 | 0.9519 | 0.9465 | 0.9809 |
| 0.0464 | 3.9869 | 2440 | 0.0755 | 0.9392 | 0.9530 | 0.9461 | 0.9811 |
| 0.0342 | 4.0196 | 2460 | 0.0771 | 0.9372 | 0.9586 | 0.9478 | 0.9807 |
| 0.0276 | 4.0523 | 2480 | 0.0767 | 0.9372 | 0.9587 | 0.9478 | 0.9804 |
| 0.0256 | 4.0850 | 2500 | 0.0786 | 0.9341 | 0.9574 | 0.9456 | 0.9800 |
| 0.0256 | 4.1176 | 2520 | 0.0810 | 0.9257 | 0.9497 | 0.9376 | 0.9786 |
| 0.0351 | 4.1503 | 2540 | 0.0735 | 0.9417 | 0.9562 | 0.9489 | 0.9819 |
| 0.0226 | 4.1830 | 2560 | 0.0757 | 0.9395 | 0.9577 | 0.9486 | 0.9813 |
| 0.0397 | 4.2157 | 2580 | 0.0792 | 0.9314 | 0.9526 | 0.9419 | 0.9799 |
| 0.0225 | 4.2484 | 2600 | 0.0758 | 0.9403 | 0.9558 | 0.9480 | 0.9812 |
| 0.0247 | 4.2810 | 2620 | 0.0766 | 0.9390 | 0.9546 | 0.9468 | 0.9811 |
| 0.0324 | 4.3137 | 2640 | 0.0754 | 0.9425 | 0.9531 | 0.9478 | 0.9814 |
| 0.0329 | 4.3464 | 2660 | 0.0763 | 0.9408 | 0.9534 | 0.9471 | 0.9808 |
| 0.0301 | 4.3791 | 2680 | 0.0765 | 0.9395 | 0.9548 | 0.9470 | 0.9807 |
| 0.0285 | 4.4118 | 2700 | 0.0763 | 0.9380 | 0.9561 | 0.9470 | 0.9811 |
| 0.019 | 4.4444 | 2720 | 0.0774 | 0.9376 | 0.9554 | 0.9464 | 0.9808 |
| 0.0187 | 4.4771 | 2740 | 0.0784 | 0.9369 | 0.9560 | 0.9463 | 0.9807 |
| 0.0261 | 4.5098 | 2760 | 0.0796 | 0.9361 | 0.9573 | 0.9466 | 0.9807 |
| 0.0352 | 4.5425 | 2780 | 0.0805 | 0.9340 | 0.9577 | 0.9458 | 0.9807 |
| 0.0269 | 4.5752 | 2800 | 0.0797 | 0.9343 | 0.9549 | 0.9445 | 0.9805 |
| 0.0317 | 4.6078 | 2820 | 0.0776 | 0.9398 | 0.9568 | 0.9482 | 0.9814 |
| 0.0297 | 4.6405 | 2840 | 0.0776 | 0.9365 | 0.9557 | 0.9460 | 0.9810 |
| 0.0221 | 4.6732 | 2860 | 0.0783 | 0.9342 | 0.9552 | 0.9446 | 0.9805 |
| 0.028 | 4.7059 | 2880 | 0.0785 | 0.9336 | 0.9560 | 0.9446 | 0.9805 |
| 0.0295 | 4.7386 | 2900 | 0.0786 | 0.9358 | 0.9570 | 0.9463 | 0.9807 |
| 0.0408 | 4.7712 | 2920 | 0.0787 | 0.9351 | 0.9579 | 0.9464 | 0.9807 |
| 0.0235 | 4.8039 | 2940 | 0.0781 | 0.9372 | 0.9585 | 0.9477 | 0.9811 |
| 0.027 | 4.8366 | 2960 | 0.0776 | 0.9388 | 0.9582 | 0.9484 | 0.9812 |
| 0.03 | 4.8693 | 2980 | 0.0775 | 0.9391 | 0.9581 | 0.9485 | 0.9813 |
| 0.0222 | 4.9020 | 3000 | 0.0773 | 0.9390 | 0.9577 | 0.9483 | 0.9812 |
| 0.0306 | 4.9346 | 3020 | 0.0772 | 0.9394 | 0.9580 | 0.9486 | 0.9814 |
| 0.0389 | 4.9673 | 3040 | 0.0772 | 0.9394 | 0.9575 | 0.9484 | 0.9814 |
### Framework versions
- PEFT 0.13.2
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0 |