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Onutoa
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1_1e-2_5_0.1

Text Classification
Transformers
PyTorch
bert
Generated from Trainer
Inference Endpoints
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+ ---
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+ license: apache-2.0
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - super_glue
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: 1_1e-2_5_0.1
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # 1_1e-2_5_0.1
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+
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+ This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the super_glue dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.8567
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+ - Accuracy: 0.7480
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.01
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+ - train_batch_size: 16
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+ - eval_batch_size: 8
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+ - seed: 11
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 100.0
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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+ | 1.682 | 1.0 | 590 | 2.1411 | 0.6208 |
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+ | 1.4095 | 2.0 | 1180 | 1.3977 | 0.3817 |
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+ | 1.1425 | 3.0 | 1770 | 0.8850 | 0.5963 |
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+ | 1.1284 | 4.0 | 2360 | 0.8549 | 0.6333 |
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+ | 0.9827 | 5.0 | 2950 | 0.8314 | 0.6511 |
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+ | 1.4181 | 6.0 | 3540 | 1.6014 | 0.3835 |
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+ | 1.0353 | 7.0 | 4130 | 1.5568 | 0.4235 |
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+ | 0.8632 | 8.0 | 4720 | 0.9442 | 0.6394 |
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+ | 0.8723 | 9.0 | 5310 | 0.7750 | 0.6905 |
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+ | 0.8161 | 10.0 | 5900 | 0.7561 | 0.6957 |
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+ | 0.7785 | 11.0 | 6490 | 0.7662 | 0.6752 |
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+ | 0.7497 | 12.0 | 7080 | 0.7282 | 0.6966 |
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+ | 0.7437 | 13.0 | 7670 | 0.7389 | 0.6798 |
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+ | 0.7156 | 14.0 | 8260 | 0.7087 | 0.7043 |
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+ | 0.6893 | 15.0 | 8850 | 0.7195 | 0.7034 |
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+ | 0.6787 | 16.0 | 9440 | 0.6835 | 0.7174 |
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+ | 0.6392 | 17.0 | 10030 | 0.6839 | 0.7162 |
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+ | 0.6287 | 18.0 | 10620 | 0.8835 | 0.6587 |
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+ | 0.6247 | 19.0 | 11210 | 0.6814 | 0.7248 |
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+ | 0.5969 | 20.0 | 11800 | 0.7200 | 0.7119 |
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+ | 0.5621 | 21.0 | 12390 | 0.6906 | 0.7284 |
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+ | 0.5461 | 22.0 | 12980 | 0.7080 | 0.7202 |
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+ | 0.5147 | 23.0 | 13570 | 0.7483 | 0.7281 |
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+ | 0.5098 | 24.0 | 14160 | 0.7129 | 0.7177 |
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+ | 0.4893 | 25.0 | 14750 | 0.7235 | 0.7346 |
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+ | 0.4723 | 26.0 | 15340 | 1.1308 | 0.6437 |
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+ | 0.4619 | 27.0 | 15930 | 0.7328 | 0.7254 |
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+ | 0.438 | 28.0 | 16520 | 0.8303 | 0.7422 |
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+ | 0.4216 | 29.0 | 17110 | 0.7223 | 0.7410 |
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+ | 0.4079 | 30.0 | 17700 | 0.7778 | 0.7315 |
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+ | 0.3803 | 31.0 | 18290 | 0.7576 | 0.7318 |
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+ | 0.3871 | 32.0 | 18880 | 0.8276 | 0.7382 |
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+ | 0.3846 | 33.0 | 19470 | 0.8631 | 0.7110 |
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+ | 0.3561 | 34.0 | 20060 | 0.8310 | 0.7211 |
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+ | 0.344 | 35.0 | 20650 | 0.7655 | 0.7364 |
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+ | 0.3333 | 36.0 | 21240 | 0.7666 | 0.7404 |
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+ | 0.3287 | 37.0 | 21830 | 0.8005 | 0.7315 |
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+ | 0.3193 | 38.0 | 22420 | 0.8775 | 0.7443 |
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+ | 0.3051 | 39.0 | 23010 | 0.8466 | 0.7428 |
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+ | 0.3019 | 40.0 | 23600 | 0.8328 | 0.7394 |
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+ | 0.2922 | 41.0 | 24190 | 0.8150 | 0.7382 |
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+ | 0.3064 | 42.0 | 24780 | 0.8742 | 0.7376 |
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+ | 0.2841 | 43.0 | 25370 | 0.7898 | 0.7361 |
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+ | 0.2841 | 44.0 | 25960 | 0.8226 | 0.7401 |
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+ | 0.2679 | 45.0 | 26550 | 0.8297 | 0.7318 |
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+ | 0.2651 | 46.0 | 27140 | 0.8316 | 0.7388 |
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+ | 0.2654 | 47.0 | 27730 | 0.8553 | 0.7364 |
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+ | 0.2457 | 48.0 | 28320 | 0.8647 | 0.7327 |
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+ | 0.2558 | 49.0 | 28910 | 0.8399 | 0.7376 |
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+ | 0.2467 | 50.0 | 29500 | 0.8517 | 0.7391 |
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+ | 0.2278 | 51.0 | 30090 | 0.8409 | 0.7275 |
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+ | 0.2343 | 52.0 | 30680 | 0.9442 | 0.7214 |
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+ | 0.2372 | 53.0 | 31270 | 0.8661 | 0.7300 |
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+ | 0.2194 | 54.0 | 31860 | 0.8430 | 0.7407 |
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+ | 0.2222 | 55.0 | 32450 | 0.9235 | 0.7242 |
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+ | 0.2328 | 56.0 | 33040 | 0.8637 | 0.7367 |
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+ | 0.2162 | 57.0 | 33630 | 0.9162 | 0.7211 |
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+ | 0.215 | 58.0 | 34220 | 0.8886 | 0.7281 |
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+ | 0.206 | 59.0 | 34810 | 0.9033 | 0.7193 |
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+ | 0.2099 | 60.0 | 35400 | 0.8829 | 0.7361 |
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+ | 0.2081 | 61.0 | 35990 | 0.8874 | 0.7367 |
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+ | 0.2105 | 62.0 | 36580 | 0.8902 | 0.7361 |
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+ | 0.1899 | 63.0 | 37170 | 0.8541 | 0.7376 |
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+ | 0.1972 | 64.0 | 37760 | 0.8740 | 0.7437 |
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+ | 0.191 | 65.0 | 38350 | 0.8897 | 0.7413 |
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+ | 0.1908 | 66.0 | 38940 | 0.8672 | 0.7437 |
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+ | 0.1894 | 67.0 | 39530 | 0.8892 | 0.7364 |
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+ | 0.1887 | 68.0 | 40120 | 0.8750 | 0.7407 |
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+ | 0.1757 | 69.0 | 40710 | 0.8887 | 0.7379 |
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+ | 0.1791 | 70.0 | 41300 | 0.8757 | 0.7413 |
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+ | 0.1848 | 71.0 | 41890 | 0.8498 | 0.7437 |
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+ | 0.1878 | 72.0 | 42480 | 0.8647 | 0.7413 |
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+ | 0.1811 | 73.0 | 43070 | 0.8715 | 0.7391 |
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+ | 0.1681 | 74.0 | 43660 | 0.9104 | 0.7416 |
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+ | 0.1693 | 75.0 | 44250 | 0.9140 | 0.7434 |
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+ | 0.1778 | 76.0 | 44840 | 0.8656 | 0.7437 |
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+ | 0.1671 | 77.0 | 45430 | 0.8830 | 0.7413 |
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+ | 0.1698 | 78.0 | 46020 | 0.8819 | 0.7431 |
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+ | 0.1641 | 79.0 | 46610 | 0.8667 | 0.7391 |
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+ | 0.1572 | 80.0 | 47200 | 0.8677 | 0.7419 |
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+ | 0.1552 | 81.0 | 47790 | 0.8704 | 0.7404 |
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+ | 0.1543 | 82.0 | 48380 | 0.8640 | 0.7489 |
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+ | 0.1576 | 83.0 | 48970 | 0.8897 | 0.7459 |
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+ | 0.153 | 84.0 | 49560 | 0.8649 | 0.7465 |
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+ | 0.1536 | 85.0 | 50150 | 0.8864 | 0.7437 |
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+ | 0.1548 | 86.0 | 50740 | 0.9050 | 0.7468 |
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+ | 0.144 | 87.0 | 51330 | 0.8696 | 0.7401 |
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+ | 0.151 | 88.0 | 51920 | 0.8987 | 0.7446 |
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+ | 0.1493 | 89.0 | 52510 | 0.8938 | 0.7431 |
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+ | 0.1455 | 90.0 | 53100 | 0.8726 | 0.7431 |
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+ | 0.1414 | 91.0 | 53690 | 0.8814 | 0.7416 |
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+ | 0.1422 | 92.0 | 54280 | 0.8838 | 0.7419 |
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+ | 0.1421 | 93.0 | 54870 | 0.8648 | 0.7465 |
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+ | 0.1477 | 94.0 | 55460 | 0.8532 | 0.7450 |
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+ | 0.1431 | 95.0 | 56050 | 0.8613 | 0.7465 |
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+ | 0.1412 | 96.0 | 56640 | 0.8708 | 0.7471 |
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+ | 0.1413 | 97.0 | 57230 | 0.8656 | 0.7468 |
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+ | 0.1375 | 98.0 | 57820 | 0.8647 | 0.7468 |
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+ | 0.1389 | 99.0 | 58410 | 0.8590 | 0.7483 |
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+ | 0.1389 | 100.0 | 59000 | 0.8567 | 0.7480 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.30.0
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+ - Pytorch 2.0.1+cu117
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+ - Datasets 2.14.4
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+ - Tokenizers 0.13.3