--- license: apache-2.0 base_model: bert-base-uncased tags: - generated_from_trainer metrics: - accuracy - f1 - precision - recall model-index: - name: BERT_top5_bm25_rr5_10_epoch results: [] --- # BERT_top5_bm25_rr5_10_epoch This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.0294 - Accuracy: 0.7708 - F1: 0.6486 - Precision: 0.5385 - Recall: 0.8155 ## 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: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 100 - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| | No log | 0.2623 | 16 | 0.6133 | 0.8237 | 0.5270 | 0.8667 | 0.3786 | | No log | 0.5246 | 32 | 0.5112 | 0.7758 | 0.2393 | 1.0 | 0.1359 | | No log | 0.7869 | 48 | 0.4725 | 0.8363 | 0.6448 | 0.7375 | 0.5728 | | No log | 1.0492 | 64 | 0.3894 | 0.8539 | 0.6882 | 0.7711 | 0.6214 | | No log | 1.3115 | 80 | 0.7018 | 0.5013 | 0.5 | 0.3379 | 0.9612 | | No log | 1.5738 | 96 | 0.4207 | 0.8338 | 0.7054 | 0.6529 | 0.7670 | | No log | 1.8361 | 112 | 0.4159 | 0.7834 | 0.6587 | 0.5570 | 0.8058 | | No log | 2.0984 | 128 | 0.4052 | 0.8060 | 0.6831 | 0.5929 | 0.8058 | | No log | 2.3607 | 144 | 0.4456 | 0.7859 | 0.6743 | 0.5570 | 0.8544 | | No log | 2.6230 | 160 | 0.3880 | 0.8564 | 0.7016 | 0.7614 | 0.6505 | | No log | 2.8852 | 176 | 0.5137 | 0.8262 | 0.5660 | 0.8036 | 0.4369 | | No log | 3.1475 | 192 | 0.4837 | 0.7935 | 0.6496 | 0.5802 | 0.7379 | | No log | 3.4098 | 208 | 0.7301 | 0.7280 | 0.6197 | 0.4862 | 0.8544 | | No log | 3.6721 | 224 | 0.6014 | 0.8413 | 0.6866 | 0.7041 | 0.6699 | | No log | 3.9344 | 240 | 0.7912 | 0.7456 | 0.6481 | 0.5054 | 0.9029 | | No log | 4.1967 | 256 | 0.6779 | 0.7834 | 0.6587 | 0.5570 | 0.8058 | | No log | 4.4590 | 272 | 0.6352 | 0.8010 | 0.6749 | 0.5857 | 0.7961 | | No log | 4.7213 | 288 | 0.9313 | 0.7229 | 0.6207 | 0.4813 | 0.8738 | | No log | 4.9836 | 304 | 0.7459 | 0.7758 | 0.6454 | 0.5473 | 0.7864 | | No log | 5.2459 | 320 | 0.6967 | 0.8186 | 0.6636 | 0.6396 | 0.6893 | | No log | 5.5082 | 336 | 0.7340 | 0.8086 | 0.6780 | 0.6015 | 0.7767 | | No log | 5.7705 | 352 | 0.9585 | 0.7506 | 0.6374 | 0.5118 | 0.8447 | | No log | 6.0328 | 368 | 0.8556 | 0.8010 | 0.6749 | 0.5857 | 0.7961 | | No log | 6.2951 | 384 | 1.0044 | 0.7758 | 0.6590 | 0.5443 | 0.8350 | | No log | 6.5574 | 400 | 1.0174 | 0.7809 | 0.6641 | 0.5513 | 0.8350 | | No log | 6.8197 | 416 | 0.8044 | 0.8111 | 0.6888 | 0.6014 | 0.8058 | | No log | 7.0820 | 432 | 1.0973 | 0.7204 | 0.6159 | 0.4785 | 0.8641 | | No log | 7.3443 | 448 | 0.9667 | 0.7758 | 0.6537 | 0.5455 | 0.8155 | | No log | 7.6066 | 464 | 0.7502 | 0.8438 | 0.7130 | 0.6814 | 0.7476 | | No log | 7.8689 | 480 | 1.0102 | 0.7733 | 0.6617 | 0.5399 | 0.8544 | | No log | 8.1311 | 496 | 0.9457 | 0.7783 | 0.6589 | 0.5484 | 0.8252 | | 0.2259 | 8.3934 | 512 | 0.9533 | 0.7834 | 0.656 | 0.5578 | 0.7961 | | 0.2259 | 8.6557 | 528 | 1.0134 | 0.7783 | 0.6589 | 0.5484 | 0.8252 | | 0.2259 | 8.9180 | 544 | 1.0594 | 0.7632 | 0.6466 | 0.5276 | 0.8350 | | 0.2259 | 9.1803 | 560 | 1.0415 | 0.7708 | 0.6566 | 0.5370 | 0.8447 | | 0.2259 | 9.4426 | 576 | 1.0485 | 0.7683 | 0.6515 | 0.5342 | 0.8350 | | 0.2259 | 9.7049 | 592 | 1.0386 | 0.7708 | 0.6540 | 0.5375 | 0.8350 | | 0.2259 | 9.9672 | 608 | 1.0294 | 0.7708 | 0.6486 | 0.5385 | 0.8155 | ### Framework versions - Transformers 4.40.1 - Pytorch 2.2.1+cu121 - Tokenizers 0.19.1