--- license: apache-2.0 base_model: distilbert-base-uncased tags: - generated_from_trainer model-index: - name: distilbert-base-uncased-finetuned-pfe-projectt results: [] --- # distilbert-base-uncased-finetuned-pfe-projectt This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.5126 - Start Accuracy: 0.7021 - End Accuracy: 0.6241 - Overall Accuracy: 0.6631 - Start Precision: 0.2862 - End Precision: 0.1446 - Start Recall: 0.3165 - End Recall: 0.1961 - Start F1 Score: 0.2802 - End F1 Score: 0.1506 ## 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: 16 - eval_batch_size: 16 - seed: 0 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 30 ### Training results | Training Loss | Epoch | Step | Validation Loss | Start Accuracy | End Accuracy | Overall Accuracy | Start Precision | End Precision | Start Recall | End Recall | Start F1 Score | End F1 Score | |:-------------:|:-----:|:----:|:---------------:|:--------------:|:------------:|:----------------:|:---------------:|:-------------:|:------------:|:----------:|:--------------:|:------------:| | 4.8235 | 1.0 | 17 | 3.6096 | 0.4752 | 0.4752 | 0.4752 | 0.0153 | 0.0140 | 0.0323 | 0.0294 | 0.0208 | 0.0189 | | 2.5596 | 2.0 | 34 | 2.5775 | 0.4752 | 0.4752 | 0.4752 | 0.0153 | 0.0140 | 0.0323 | 0.0294 | 0.0208 | 0.0189 | | 2.0949 | 3.0 | 51 | 2.2935 | 0.4752 | 0.4752 | 0.4752 | 0.0153 | 0.0140 | 0.0323 | 0.0294 | 0.0208 | 0.0189 | | 1.9248 | 4.0 | 68 | 2.1906 | 0.4752 | 0.4752 | 0.4752 | 0.0153 | 0.0140 | 0.0323 | 0.0294 | 0.0208 | 0.0189 | | 1.7309 | 5.0 | 85 | 2.0463 | 0.5674 | 0.4752 | 0.5213 | 0.0978 | 0.0140 | 0.1340 | 0.0294 | 0.1110 | 0.0189 | | 1.5193 | 6.0 | 102 | 1.9047 | 0.5745 | 0.4823 | 0.5284 | 0.1116 | 0.0390 | 0.1544 | 0.0657 | 0.1240 | 0.0438 | | 1.4401 | 7.0 | 119 | 1.8648 | 0.5532 | 0.5035 | 0.5284 | 0.0960 | 0.0686 | 0.1271 | 0.0858 | 0.1046 | 0.0676 | | 1.3916 | 8.0 | 136 | 1.7904 | 0.6170 | 0.5532 | 0.5851 | 0.1673 | 0.0709 | 0.2090 | 0.1041 | 0.1800 | 0.0795 | | 1.2498 | 9.0 | 153 | 1.8084 | 0.6170 | 0.5816 | 0.5993 | 0.1309 | 0.0862 | 0.1791 | 0.1145 | 0.1449 | 0.0930 | | 1.1733 | 10.0 | 170 | 1.7518 | 0.6241 | 0.5957 | 0.6099 | 0.1586 | 0.0925 | 0.2032 | 0.1221 | 0.1712 | 0.0995 | | 1.0563 | 11.0 | 187 | 1.6420 | 0.6241 | 0.5816 | 0.6028 | 0.1673 | 0.0918 | 0.2206 | 0.1337 | 0.1814 | 0.1047 | | 1.0074 | 12.0 | 204 | 1.8142 | 0.6454 | 0.6099 | 0.6277 | 0.1453 | 0.0934 | 0.1737 | 0.1080 | 0.1497 | 0.0982 | | 0.9473 | 13.0 | 221 | 1.6035 | 0.6738 | 0.6241 | 0.6489 | 0.2440 | 0.1010 | 0.2606 | 0.1444 | 0.2340 | 0.1138 | | 0.9307 | 14.0 | 238 | 1.4999 | 0.6809 | 0.6241 | 0.6525 | 0.2226 | 0.1151 | 0.2484 | 0.1418 | 0.2225 | 0.1141 | | 0.8668 | 15.0 | 255 | 1.5837 | 0.6950 | 0.6312 | 0.6631 | 0.2456 | 0.1033 | 0.2678 | 0.1520 | 0.2395 | 0.1162 | | 0.8226 | 16.0 | 272 | 1.5517 | 0.6879 | 0.6312 | 0.6596 | 0.2741 | 0.1385 | 0.2911 | 0.1955 | 0.2523 | 0.1451 | | 0.7358 | 17.0 | 289 | 1.5387 | 0.7092 | 0.6241 | 0.6667 | 0.3022 | 0.1374 | 0.3360 | 0.1898 | 0.2854 | 0.1424 | | 0.7529 | 18.0 | 306 | 1.4644 | 0.6950 | 0.6383 | 0.6667 | 0.2554 | 0.1358 | 0.3011 | 0.1947 | 0.2531 | 0.1450 | | 0.6962 | 19.0 | 323 | 1.5374 | 0.6809 | 0.6383 | 0.6596 | 0.2570 | 0.1419 | 0.2890 | 0.1861 | 0.2516 | 0.1502 | | 0.6807 | 20.0 | 340 | 1.4873 | 0.6809 | 0.6383 | 0.6596 | 0.2577 | 0.1469 | 0.3058 | 0.1840 | 0.2623 | 0.1572 | | 0.6988 | 21.0 | 357 | 1.5178 | 0.6667 | 0.6099 | 0.6383 | 0.2843 | 0.1558 | 0.3050 | 0.1982 | 0.2802 | 0.1597 | | 0.6632 | 22.0 | 374 | 1.5319 | 0.7092 | 0.6312 | 0.6702 | 0.2860 | 0.1489 | 0.3053 | 0.2015 | 0.2788 | 0.1628 | | 0.6081 | 23.0 | 391 | 1.5817 | 0.7021 | 0.6454 | 0.6738 | 0.2537 | 0.1767 | 0.2853 | 0.1944 | 0.2489 | 0.1677 | | 0.5926 | 24.0 | 408 | 1.5514 | 0.6950 | 0.6241 | 0.6596 | 0.3069 | 0.1451 | 0.3160 | 0.1913 | 0.2937 | 0.1465 | | 0.6449 | 25.0 | 425 | 1.5521 | 0.6950 | 0.6383 | 0.6667 | 0.2826 | 0.1687 | 0.3336 | 0.2133 | 0.2806 | 0.1654 | | 0.5542 | 26.0 | 442 | 1.4860 | 0.7305 | 0.6383 | 0.6844 | 0.3305 | 0.1598 | 0.3734 | 0.1812 | 0.3257 | 0.1580 | | 0.5668 | 27.0 | 459 | 1.5091 | 0.7092 | 0.6454 | 0.6773 | 0.3201 | 0.1688 | 0.3304 | 0.2075 | 0.2982 | 0.1670 | | 0.5603 | 28.0 | 476 | 1.5088 | 0.7021 | 0.6454 | 0.6738 | 0.2819 | 0.1535 | 0.3165 | 0.2022 | 0.2772 | 0.1569 | | 0.5353 | 29.0 | 493 | 1.5101 | 0.7021 | 0.6383 | 0.6702 | 0.2862 | 0.1447 | 0.3165 | 0.1968 | 0.2802 | 0.1494 | | 0.5082 | 30.0 | 510 | 1.5126 | 0.7021 | 0.6241 | 0.6631 | 0.2862 | 0.1446 | 0.3165 | 0.1961 | 0.2802 | 0.1506 | ### Framework versions - Transformers 4.39.3 - Pytorch 2.1.2 - Datasets 2.18.0 - Tokenizers 0.15.2