--- license: apache-2.0 base_model: t5-base tags: - generated_from_trainer metrics: - accuracy - f1 - precision - recall model-index: - name: TTC4900Model results: [] --- # TTC4900Model This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.5372 - Accuracy: 0.8371 - F1: 0.7316 - Precision: 0.7615 - Recall: 0.7112 ## 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: 32 - eval_batch_size: 64 - 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: 3 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| | 1.4792 | 0.04 | 50 | 1.3375 | 0.5157 | 0.1525 | 0.2666 | 0.2006 | | 1.2938 | 0.08 | 100 | 1.1358 | 0.6112 | 0.2290 | 0.4100 | 0.2395 | | 1.1393 | 0.12 | 150 | 1.0186 | 0.6552 | 0.4235 | 0.5382 | 0.4140 | | 1.0714 | 0.16 | 200 | 0.9367 | 0.7043 | 0.4586 | 0.5566 | 0.4520 | | 0.9874 | 0.2 | 250 | 0.8549 | 0.7151 | 0.4912 | 0.7129 | 0.4745 | | 0.8875 | 0.24 | 300 | 0.7741 | 0.7479 | 0.5512 | 0.6722 | 0.5300 | | 0.8267 | 0.28 | 350 | 0.7463 | 0.7497 | 0.5841 | 0.6718 | 0.5784 | | 0.798 | 0.33 | 400 | 0.7388 | 0.7559 | 0.5798 | 0.6802 | 0.5712 | | 0.778 | 0.37 | 450 | 0.7351 | 0.7668 | 0.5795 | 0.7799 | 0.5318 | | 0.7568 | 0.41 | 500 | 0.7147 | 0.7792 | 0.5958 | 0.7228 | 0.5931 | | 0.721 | 0.45 | 550 | 0.8179 | 0.7299 | 0.5823 | 0.6824 | 0.5868 | | 0.7534 | 0.49 | 600 | 0.6631 | 0.7874 | 0.6106 | 0.7809 | 0.5804 | | 0.7242 | 0.53 | 650 | 0.6918 | 0.7843 | 0.5966 | 0.7648 | 0.5666 | | 0.7236 | 0.57 | 700 | 0.7457 | 0.7733 | 0.5752 | 0.7704 | 0.5465 | | 0.702 | 0.61 | 750 | 0.6810 | 0.7928 | 0.6059 | 0.7791 | 0.5692 | | 0.6681 | 0.65 | 800 | 0.6318 | 0.8029 | 0.6441 | 0.7699 | 0.6255 | | 0.6463 | 0.69 | 850 | 0.6754 | 0.7968 | 0.6387 | 0.7553 | 0.6412 | | 0.7443 | 0.73 | 900 | 0.7580 | 0.7720 | 0.5804 | 0.7278 | 0.5933 | | 0.7273 | 0.77 | 950 | 0.6410 | 0.8082 | 0.6364 | 0.7804 | 0.6112 | | 0.6329 | 0.81 | 1000 | 0.6294 | 0.8028 | 0.6452 | 0.7305 | 0.6362 | | 0.6623 | 0.85 | 1050 | 0.6742 | 0.7797 | 0.5614 | 0.8038 | 0.5437 | | 0.6198 | 0.89 | 1100 | 0.6250 | 0.8048 | 0.6306 | 0.7658 | 0.6202 | | 0.614 | 0.93 | 1150 | 0.7138 | 0.7852 | 0.6231 | 0.6792 | 0.6433 | | 0.6423 | 0.98 | 1200 | 0.6581 | 0.7991 | 0.6601 | 0.7570 | 0.6526 | | 0.6175 | 1.02 | 1250 | 0.6336 | 0.8107 | 0.6790 | 0.7297 | 0.6737 | | 0.5583 | 1.06 | 1300 | 0.6364 | 0.8074 | 0.6505 | 0.7822 | 0.6284 | | 0.5371 | 1.1 | 1350 | 0.6051 | 0.8158 | 0.6878 | 0.7743 | 0.6513 | | 0.5173 | 1.14 | 1400 | 0.6464 | 0.7972 | 0.6981 | 0.7249 | 0.7007 | | 0.5602 | 1.18 | 1450 | 0.6631 | 0.7928 | 0.6419 | 0.7471 | 0.6506 | | 0.5187 | 1.22 | 1500 | 0.6140 | 0.8164 | 0.6756 | 0.7739 | 0.6674 | | 0.6183 | 1.26 | 1550 | 0.6166 | 0.8170 | 0.6782 | 0.7513 | 0.6611 | | 0.4991 | 1.3 | 1600 | 0.6289 | 0.8198 | 0.6920 | 0.8022 | 0.6470 | | 0.5449 | 1.34 | 1650 | 0.6011 | 0.8194 | 0.6995 | 0.7613 | 0.6684 | | 0.5358 | 1.38 | 1700 | 0.6036 | 0.8110 | 0.7041 | 0.7335 | 0.6973 | | 0.5451 | 1.42 | 1750 | 0.6156 | 0.8141 | 0.6392 | 0.8173 | 0.6160 | | 0.5421 | 1.46 | 1800 | 0.5723 | 0.8252 | 0.7149 | 0.7704 | 0.6930 | | 0.5199 | 1.5 | 1850 | 0.6290 | 0.8129 | 0.6658 | 0.7989 | 0.6102 | | 0.5477 | 1.54 | 1900 | 0.5792 | 0.8222 | 0.7008 | 0.7831 | 0.6682 | | 0.5117 | 1.59 | 1950 | 0.5652 | 0.8288 | 0.7119 | 0.7801 | 0.6796 | | 0.5201 | 1.63 | 2000 | 0.5661 | 0.8276 | 0.7143 | 0.7802 | 0.6871 | | 0.5098 | 1.67 | 2050 | 0.5745 | 0.8265 | 0.6906 | 0.7897 | 0.6591 | | 0.5226 | 1.71 | 2100 | 0.5768 | 0.8251 | 0.6948 | 0.7516 | 0.6903 | | 0.5367 | 1.75 | 2150 | 0.5573 | 0.8318 | 0.7180 | 0.7886 | 0.6879 | | 0.5484 | 1.79 | 2200 | 0.5738 | 0.8241 | 0.6990 | 0.7818 | 0.6638 | | 0.534 | 1.83 | 2250 | 0.5601 | 0.8299 | 0.7167 | 0.7799 | 0.6898 | | 0.5423 | 1.87 | 2300 | 0.5571 | 0.8240 | 0.7228 | 0.7592 | 0.7153 | | 0.5056 | 1.91 | 2350 | 0.5635 | 0.8267 | 0.7004 | 0.8005 | 0.6642 | | 0.5355 | 1.95 | 2400 | 0.5546 | 0.8275 | 0.7167 | 0.7681 | 0.7053 | | 0.5387 | 1.99 | 2450 | 0.5417 | 0.8315 | 0.7277 | 0.7656 | 0.7028 | | 0.4148 | 2.03 | 2500 | 0.6051 | 0.8310 | 0.7170 | 0.7716 | 0.6878 | | 0.4685 | 2.07 | 2550 | 0.5605 | 0.8302 | 0.7139 | 0.7818 | 0.6980 | | 0.5007 | 2.11 | 2600 | 0.5530 | 0.8326 | 0.7288 | 0.7650 | 0.7165 | | 0.4524 | 2.15 | 2650 | 0.5648 | 0.8302 | 0.7188 | 0.7680 | 0.6941 | | 0.4437 | 2.2 | 2700 | 0.5636 | 0.8275 | 0.7287 | 0.7684 | 0.7171 | | 0.4326 | 2.24 | 2750 | 0.5542 | 0.8341 | 0.7166 | 0.7889 | 0.6903 | | 0.4182 | 2.28 | 2800 | 0.5697 | 0.8272 | 0.7283 | 0.7398 | 0.7227 | | 0.4466 | 2.32 | 2850 | 0.5628 | 0.8343 | 0.7257 | 0.7925 | 0.6958 | | 0.4118 | 2.36 | 2900 | 0.5717 | 0.8266 | 0.7249 | 0.7334 | 0.7250 | | 0.3689 | 2.4 | 2950 | 0.5716 | 0.8342 | 0.7259 | 0.7705 | 0.7105 | | 0.4332 | 2.44 | 3000 | 0.5557 | 0.8345 | 0.7316 | 0.7586 | 0.7192 | | 0.3926 | 2.48 | 3050 | 0.5635 | 0.8352 | 0.7266 | 0.7762 | 0.7071 | | 0.4141 | 2.52 | 3100 | 0.5553 | 0.8354 | 0.7273 | 0.7732 | 0.6983 | | 0.3984 | 2.56 | 3150 | 0.5605 | 0.8349 | 0.7343 | 0.7670 | 0.7142 | | 0.4267 | 2.6 | 3200 | 0.5478 | 0.8376 | 0.7325 | 0.7828 | 0.7054 | | 0.4309 | 2.64 | 3250 | 0.5512 | 0.8339 | 0.7341 | 0.7672 | 0.7155 | | 0.408 | 2.68 | 3300 | 0.5598 | 0.8351 | 0.7339 | 0.7637 | 0.7134 | | 0.4174 | 2.72 | 3350 | 0.5553 | 0.8320 | 0.7374 | 0.7668 | 0.7206 | | 0.3979 | 2.76 | 3400 | 0.5559 | 0.8357 | 0.7342 | 0.7713 | 0.7151 | | 0.4021 | 2.8 | 3450 | 0.5500 | 0.8356 | 0.7364 | 0.7595 | 0.7259 | | 0.4018 | 2.85 | 3500 | 0.5485 | 0.8371 | 0.7356 | 0.7715 | 0.7151 | | 0.392 | 2.89 | 3550 | 0.5566 | 0.8348 | 0.7368 | 0.7627 | 0.7252 | | 0.3695 | 2.93 | 3600 | 0.5548 | 0.8355 | 0.7380 | 0.7614 | 0.7251 | | 0.3936 | 2.97 | 3650 | 0.5503 | 0.8353 | 0.7387 | 0.7627 | 0.7256 | ### Framework versions - Transformers 4.38.2 - Pytorch 2.1.2 - Datasets 2.1.0 - Tokenizers 0.15.2