--- license: mit base_model: microsoft/Multilingual-MiniLM-L12-H384 tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: ner-coin results: [] --- # ner-coin This model is a fine-tuned version of [microsoft/Multilingual-MiniLM-L12-H384](https://huggingface.co/microsoft/Multilingual-MiniLM-L12-H384) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.0336 - Precision: 0.9730 - Recall: 0.9789 - F1: 0.9759 - Accuracy: 0.9937 ## 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 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 100 ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | No log | 1.0 | 26 | 0.2470 | 0.7608 | 0.8733 | 0.8132 | 0.9776 | | No log | 2.0 | 52 | 0.1881 | 0.7803 | 0.8733 | 0.8242 | 0.9817 | | No log | 3.0 | 78 | 0.1495 | 0.9629 | 0.9789 | 0.9708 | 0.9929 | | No log | 4.0 | 104 | 0.1277 | 0.9744 | 0.9759 | 0.9751 | 0.9942 | | No log | 5.0 | 130 | 0.1107 | 0.9745 | 0.9804 | 0.9774 | 0.9949 | | No log | 6.0 | 156 | 0.1004 | 0.9688 | 0.9819 | 0.9753 | 0.9940 | | No log | 7.0 | 182 | 0.0895 | 0.9701 | 0.9804 | 0.9752 | 0.9942 | | No log | 8.0 | 208 | 0.0808 | 0.9745 | 0.9789 | 0.9767 | 0.9949 | | No log | 9.0 | 234 | 0.0731 | 0.9744 | 0.9774 | 0.9759 | 0.9947 | | No log | 10.0 | 260 | 0.0720 | 0.9731 | 0.9819 | 0.9775 | 0.9939 | | No log | 11.0 | 286 | 0.0662 | 0.9731 | 0.9819 | 0.9775 | 0.9940 | | No log | 12.0 | 312 | 0.0589 | 0.9804 | 0.9804 | 0.9804 | 0.9955 | | No log | 13.0 | 338 | 0.0573 | 0.9746 | 0.9819 | 0.9782 | 0.9945 | | No log | 14.0 | 364 | 0.0520 | 0.9789 | 0.9789 | 0.9789 | 0.9945 | | No log | 15.0 | 390 | 0.0507 | 0.9803 | 0.9774 | 0.9789 | 0.9947 | | No log | 16.0 | 416 | 0.0475 | 0.9804 | 0.9789 | 0.9796 | 0.9949 | | No log | 17.0 | 442 | 0.0461 | 0.9731 | 0.9804 | 0.9767 | 0.9944 | | No log | 18.0 | 468 | 0.0435 | 0.9773 | 0.9744 | 0.9758 | 0.9947 | | No log | 19.0 | 494 | 0.0400 | 0.9760 | 0.9819 | 0.9789 | 0.9952 | | 0.1028 | 20.0 | 520 | 0.0390 | 0.9834 | 0.9819 | 0.9826 | 0.9960 | | 0.1028 | 21.0 | 546 | 0.0386 | 0.9716 | 0.9804 | 0.9760 | 0.9945 | | 0.1028 | 22.0 | 572 | 0.0373 | 0.9688 | 0.9834 | 0.9760 | 0.9942 | | 0.1028 | 23.0 | 598 | 0.0355 | 0.9789 | 0.9804 | 0.9797 | 0.9950 | | 0.1028 | 24.0 | 624 | 0.0381 | 0.9617 | 0.9834 | 0.9724 | 0.9924 | | 0.1028 | 25.0 | 650 | 0.0328 | 0.9775 | 0.9819 | 0.9797 | 0.9950 | | 0.1028 | 26.0 | 676 | 0.0329 | 0.9789 | 0.9804 | 0.9797 | 0.9952 | | 0.1028 | 27.0 | 702 | 0.0357 | 0.9789 | 0.9804 | 0.9797 | 0.9950 | | 0.1028 | 28.0 | 728 | 0.0357 | 0.9688 | 0.9849 | 0.9768 | 0.9940 | | 0.1028 | 29.0 | 754 | 0.0382 | 0.9632 | 0.9864 | 0.9747 | 0.9921 | | 0.1028 | 30.0 | 780 | 0.0303 | 0.9789 | 0.9819 | 0.9804 | 0.9953 | | 0.1028 | 31.0 | 806 | 0.0289 | 0.9819 | 0.9819 | 0.9819 | 0.9957 | | 0.1028 | 32.0 | 832 | 0.0296 | 0.9790 | 0.9834 | 0.9812 | 0.9955 | | 0.1028 | 33.0 | 858 | 0.0290 | 0.9848 | 0.9789 | 0.9818 | 0.9953 | | 0.1028 | 34.0 | 884 | 0.0301 | 0.9789 | 0.9819 | 0.9804 | 0.9953 | | 0.1028 | 35.0 | 910 | 0.0294 | 0.9702 | 0.9834 | 0.9768 | 0.9944 | | 0.1028 | 36.0 | 936 | 0.0347 | 0.9717 | 0.9834 | 0.9775 | 0.9936 | | 0.1028 | 37.0 | 962 | 0.0303 | 0.9746 | 0.9819 | 0.9782 | 0.9939 | | 0.1028 | 38.0 | 988 | 0.0344 | 0.9645 | 0.9849 | 0.9746 | 0.9923 | | 0.0209 | 39.0 | 1014 | 0.0300 | 0.9717 | 0.9834 | 0.9775 | 0.9937 | | 0.0209 | 40.0 | 1040 | 0.0288 | 0.9789 | 0.9819 | 0.9804 | 0.9950 | | 0.0209 | 41.0 | 1066 | 0.0289 | 0.9804 | 0.9819 | 0.9812 | 0.9952 | | 0.0209 | 42.0 | 1092 | 0.0296 | 0.9716 | 0.9804 | 0.9760 | 0.9939 | | 0.0209 | 43.0 | 1118 | 0.0319 | 0.9659 | 0.9834 | 0.9746 | 0.9928 | | 0.0209 | 44.0 | 1144 | 0.0269 | 0.9848 | 0.9759 | 0.9803 | 0.9950 | | 0.0209 | 45.0 | 1170 | 0.0259 | 0.9804 | 0.9804 | 0.9804 | 0.9950 | | 0.0209 | 46.0 | 1196 | 0.0306 | 0.9716 | 0.9819 | 0.9767 | 0.9939 | | 0.0209 | 47.0 | 1222 | 0.0354 | 0.9658 | 0.9789 | 0.9723 | 0.9918 | | 0.0209 | 48.0 | 1248 | 0.0280 | 0.9746 | 0.9819 | 0.9782 | 0.9937 | | 0.0209 | 49.0 | 1274 | 0.0266 | 0.9833 | 0.9774 | 0.9803 | 0.9955 | | 0.0209 | 50.0 | 1300 | 0.0287 | 0.9760 | 0.9819 | 0.9789 | 0.9945 | | 0.0209 | 51.0 | 1326 | 0.0280 | 0.9818 | 0.9759 | 0.9788 | 0.9950 | | 0.0209 | 52.0 | 1352 | 0.0316 | 0.9787 | 0.9713 | 0.9750 | 0.9937 | | 0.0209 | 53.0 | 1378 | 0.0302 | 0.9744 | 0.9774 | 0.9759 | 0.9936 | | 0.0209 | 54.0 | 1404 | 0.0309 | 0.9744 | 0.9759 | 0.9751 | 0.9932 | | 0.0209 | 55.0 | 1430 | 0.0298 | 0.9818 | 0.9759 | 0.9788 | 0.9947 | | 0.0209 | 56.0 | 1456 | 0.0291 | 0.9729 | 0.9744 | 0.9736 | 0.9931 | | 0.0209 | 57.0 | 1482 | 0.0287 | 0.9773 | 0.9759 | 0.9766 | 0.9937 | | 0.0099 | 58.0 | 1508 | 0.0349 | 0.9687 | 0.9789 | 0.9737 | 0.9921 | | 0.0099 | 59.0 | 1534 | 0.0295 | 0.9745 | 0.9789 | 0.9767 | 0.9936 | | 0.0099 | 60.0 | 1560 | 0.0306 | 0.9759 | 0.9789 | 0.9774 | 0.9936 | | 0.0099 | 61.0 | 1586 | 0.0298 | 0.9775 | 0.9819 | 0.9797 | 0.9944 | | 0.0099 | 62.0 | 1612 | 0.0296 | 0.9746 | 0.9819 | 0.9782 | 0.9944 | | 0.0099 | 63.0 | 1638 | 0.0282 | 0.9760 | 0.9804 | 0.9782 | 0.9944 | | 0.0099 | 64.0 | 1664 | 0.0290 | 0.9804 | 0.9804 | 0.9804 | 0.9949 | | 0.0099 | 65.0 | 1690 | 0.0290 | 0.9745 | 0.9789 | 0.9767 | 0.9937 | | 0.0099 | 66.0 | 1716 | 0.0277 | 0.9774 | 0.9789 | 0.9781 | 0.9944 | | 0.0099 | 67.0 | 1742 | 0.0303 | 0.9745 | 0.9804 | 0.9774 | 0.9942 | | 0.0099 | 68.0 | 1768 | 0.0283 | 0.9773 | 0.9759 | 0.9766 | 0.9945 | | 0.0099 | 69.0 | 1794 | 0.0301 | 0.9759 | 0.9774 | 0.9766 | 0.9940 | | 0.0099 | 70.0 | 1820 | 0.0304 | 0.9745 | 0.9789 | 0.9767 | 0.9940 | | 0.0099 | 71.0 | 1846 | 0.0290 | 0.9789 | 0.9774 | 0.9781 | 0.9944 | | 0.0099 | 72.0 | 1872 | 0.0346 | 0.9658 | 0.9789 | 0.9723 | 0.9926 | | 0.0099 | 73.0 | 1898 | 0.0327 | 0.9687 | 0.9789 | 0.9737 | 0.9932 | | 0.0099 | 74.0 | 1924 | 0.0315 | 0.9759 | 0.9789 | 0.9774 | 0.9940 | | 0.0099 | 75.0 | 1950 | 0.0305 | 0.9774 | 0.9774 | 0.9774 | 0.9940 | | 0.0099 | 76.0 | 1976 | 0.0304 | 0.9759 | 0.9789 | 0.9774 | 0.9942 | | 0.0059 | 77.0 | 2002 | 0.0306 | 0.9716 | 0.9789 | 0.9752 | 0.9936 | | 0.0059 | 78.0 | 2028 | 0.0304 | 0.9789 | 0.9789 | 0.9789 | 0.9944 | | 0.0059 | 79.0 | 2054 | 0.0322 | 0.9687 | 0.9789 | 0.9737 | 0.9932 | | 0.0059 | 80.0 | 2080 | 0.0323 | 0.9730 | 0.9789 | 0.9759 | 0.9936 | | 0.0059 | 81.0 | 2106 | 0.0314 | 0.9730 | 0.9789 | 0.9759 | 0.9937 | | 0.0059 | 82.0 | 2132 | 0.0315 | 0.9730 | 0.9789 | 0.9759 | 0.9937 | | 0.0059 | 83.0 | 2158 | 0.0310 | 0.9731 | 0.9804 | 0.9767 | 0.9939 | | 0.0059 | 84.0 | 2184 | 0.0318 | 0.9701 | 0.9804 | 0.9752 | 0.9936 | | 0.0059 | 85.0 | 2210 | 0.0317 | 0.9745 | 0.9789 | 0.9767 | 0.9939 | | 0.0059 | 86.0 | 2236 | 0.0316 | 0.9745 | 0.9789 | 0.9767 | 0.9939 | | 0.0059 | 87.0 | 2262 | 0.0318 | 0.9745 | 0.9789 | 0.9767 | 0.9939 | | 0.0059 | 88.0 | 2288 | 0.0324 | 0.9730 | 0.9789 | 0.9759 | 0.9937 | | 0.0059 | 89.0 | 2314 | 0.0320 | 0.9745 | 0.9789 | 0.9767 | 0.9939 | | 0.0059 | 90.0 | 2340 | 0.0336 | 0.9701 | 0.9789 | 0.9745 | 0.9934 | | 0.0059 | 91.0 | 2366 | 0.0335 | 0.9730 | 0.9789 | 0.9759 | 0.9937 | | 0.0059 | 92.0 | 2392 | 0.0332 | 0.9745 | 0.9789 | 0.9767 | 0.9939 | | 0.0059 | 93.0 | 2418 | 0.0334 | 0.9730 | 0.9789 | 0.9759 | 0.9937 | | 0.0059 | 94.0 | 2444 | 0.0335 | 0.9716 | 0.9789 | 0.9752 | 0.9936 | | 0.0059 | 95.0 | 2470 | 0.0342 | 0.9701 | 0.9789 | 0.9745 | 0.9931 | | 0.0059 | 96.0 | 2496 | 0.0338 | 0.9716 | 0.9789 | 0.9752 | 0.9936 | | 0.0045 | 97.0 | 2522 | 0.0338 | 0.9730 | 0.9789 | 0.9759 | 0.9937 | | 0.0045 | 98.0 | 2548 | 0.0338 | 0.9716 | 0.9789 | 0.9752 | 0.9936 | | 0.0045 | 99.0 | 2574 | 0.0336 | 0.9730 | 0.9789 | 0.9759 | 0.9937 | | 0.0045 | 100.0 | 2600 | 0.0336 | 0.9730 | 0.9789 | 0.9759 | 0.9937 | ### Framework versions - Transformers 4.40.2 - Pytorch 2.1.0+cu121 - Datasets 2.14.5 - Tokenizers 0.19.1