--- license: apache-2.0 tags: - generated_from_trainer model-index: - name: bert-finetuned-ner results: [] --- # bert-finetuned-ner This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.7230 ## 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: 2e-05 - 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: 100 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | No log | 1.0 | 68 | 7.5711 | | No log | 2.0 | 136 | 7.5137 | | No log | 3.0 | 204 | 7.4045 | | No log | 4.0 | 272 | 7.2699 | | No log | 5.0 | 340 | 7.1041 | | No log | 6.0 | 408 | 6.9418 | | No log | 7.0 | 476 | 6.7958 | | 7.5401 | 8.0 | 544 | 6.6459 | | 7.5401 | 9.0 | 612 | 6.5085 | | 7.5401 | 10.0 | 680 | 6.3777 | | 7.5401 | 11.0 | 748 | 6.2365 | | 7.5401 | 12.0 | 816 | 6.1106 | | 7.5401 | 13.0 | 884 | 5.9833 | | 7.5401 | 14.0 | 952 | 5.8674 | | 6.5715 | 15.0 | 1020 | 5.7555 | | 6.5715 | 16.0 | 1088 | 5.6403 | | 6.5715 | 17.0 | 1156 | 5.5376 | | 6.5715 | 18.0 | 1224 | 5.4137 | | 6.5715 | 19.0 | 1292 | 5.3225 | | 6.5715 | 20.0 | 1360 | 5.2182 | | 6.5715 | 21.0 | 1428 | 5.1122 | | 6.5715 | 22.0 | 1496 | 5.0065 | | 5.7874 | 23.0 | 1564 | 4.9041 | | 5.7874 | 24.0 | 1632 | 4.8166 | | 5.7874 | 25.0 | 1700 | 4.7134 | | 5.7874 | 26.0 | 1768 | 4.6366 | | 5.7874 | 27.0 | 1836 | 4.5368 | | 5.7874 | 28.0 | 1904 | 4.4495 | | 5.7874 | 29.0 | 1972 | 4.3610 | | 5.0922 | 30.0 | 2040 | 4.2840 | | 5.0922 | 31.0 | 2108 | 4.1986 | | 5.0922 | 32.0 | 2176 | 4.1160 | | 5.0922 | 33.0 | 2244 | 4.0367 | | 5.0922 | 34.0 | 2312 | 3.9648 | | 5.0922 | 35.0 | 2380 | 3.8908 | | 5.0922 | 36.0 | 2448 | 3.8100 | | 4.4927 | 37.0 | 2516 | 3.7385 | | 4.4927 | 38.0 | 2584 | 3.6692 | | 4.4927 | 39.0 | 2652 | 3.6037 | | 4.4927 | 40.0 | 2720 | 3.5427 | | 4.4927 | 41.0 | 2788 | 3.4718 | | 4.4927 | 42.0 | 2856 | 3.4000 | | 4.4927 | 43.0 | 2924 | 3.3363 | | 4.4927 | 44.0 | 2992 | 3.2797 | | 3.9767 | 45.0 | 3060 | 3.2366 | | 3.9767 | 46.0 | 3128 | 3.1579 | | 3.9767 | 47.0 | 3196 | 3.0965 | | 3.9767 | 48.0 | 3264 | 3.0387 | | 3.9767 | 49.0 | 3332 | 2.9887 | | 3.9767 | 50.0 | 3400 | 2.9314 | | 3.9767 | 51.0 | 3468 | 2.8779 | | 3.5181 | 52.0 | 3536 | 2.8385 | | 3.5181 | 53.0 | 3604 | 2.7807 | | 3.5181 | 54.0 | 3672 | 2.7384 | | 3.5181 | 55.0 | 3740 | 2.6938 | | 3.5181 | 56.0 | 3808 | 2.6386 | | 3.5181 | 57.0 | 3876 | 2.6043 | | 3.5181 | 58.0 | 3944 | 2.5500 | | 3.1415 | 59.0 | 4012 | 2.5146 | | 3.1415 | 60.0 | 4080 | 2.4785 | | 3.1415 | 61.0 | 4148 | 2.4321 | | 3.1415 | 62.0 | 4216 | 2.3939 | | 3.1415 | 63.0 | 4284 | 2.3641 | | 3.1415 | 64.0 | 4352 | 2.3193 | | 3.1415 | 65.0 | 4420 | 2.2894 | | 3.1415 | 66.0 | 4488 | 2.2563 | | 2.8316 | 67.0 | 4556 | 2.2242 | | 2.8316 | 68.0 | 4624 | 2.1952 | | 2.8316 | 69.0 | 4692 | 2.1640 | | 2.8316 | 70.0 | 4760 | 2.1346 | | 2.8316 | 71.0 | 4828 | 2.1069 | | 2.8316 | 72.0 | 4896 | 2.0837 | | 2.8316 | 73.0 | 4964 | 2.0536 | | 2.5874 | 74.0 | 5032 | 2.0310 | | 2.5874 | 75.0 | 5100 | 2.0053 | | 2.5874 | 76.0 | 5168 | 1.9829 | | 2.5874 | 77.0 | 5236 | 1.9605 | | 2.5874 | 78.0 | 5304 | 1.9421 | | 2.5874 | 79.0 | 5372 | 1.9192 | | 2.5874 | 80.0 | 5440 | 1.9045 | | 2.3824 | 81.0 | 5508 | 1.8918 | | 2.3824 | 82.0 | 5576 | 1.8708 | | 2.3824 | 83.0 | 5644 | 1.8547 | | 2.3824 | 84.0 | 5712 | 1.8397 | | 2.3824 | 85.0 | 5780 | 1.8275 | | 2.3824 | 86.0 | 5848 | 1.8078 | | 2.3824 | 87.0 | 5916 | 1.8017 | | 2.3824 | 88.0 | 5984 | 1.7901 | | 2.2537 | 89.0 | 6052 | 1.7802 | | 2.2537 | 90.0 | 6120 | 1.7678 | | 2.2537 | 91.0 | 6188 | 1.7610 | | 2.2537 | 92.0 | 6256 | 1.7523 | | 2.2537 | 93.0 | 6324 | 1.7447 | | 2.2537 | 94.0 | 6392 | 1.7385 | | 2.2537 | 95.0 | 6460 | 1.7343 | | 2.1756 | 96.0 | 6528 | 1.7286 | | 2.1756 | 97.0 | 6596 | 1.7267 | | 2.1756 | 98.0 | 6664 | 1.7239 | | 2.1756 | 99.0 | 6732 | 1.7233 | | 2.1756 | 100.0 | 6800 | 1.7230 | ### Framework versions - Transformers 4.26.1 - Pytorch 1.13.1+cu116 - Datasets 2.10.1 - Tokenizers 0.13.2