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Onutoa
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1_9e-3_5_0.5

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_9e-3_5_0.5
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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_9e-3_5_0.5
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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: 0.8603
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+ - Accuracy: 0.7489
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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: 0.009
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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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+ | 2.7616 | 1.0 | 590 | 2.7583 | 0.3798 |
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+ | 2.2507 | 2.0 | 1180 | 1.8432 | 0.6294 |
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+ | 2.5953 | 3.0 | 1770 | 3.4928 | 0.4532 |
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+ | 2.3305 | 4.0 | 2360 | 1.5737 | 0.6486 |
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+ | 1.9577 | 5.0 | 2950 | 2.6604 | 0.6263 |
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+ | 1.7557 | 6.0 | 3540 | 1.2734 | 0.6761 |
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+ | 1.6227 | 7.0 | 4130 | 3.4140 | 0.5119 |
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+ | 1.4961 | 8.0 | 4720 | 1.2029 | 0.7043 |
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+ | 1.3331 | 9.0 | 5310 | 1.2170 | 0.7092 |
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+ | 1.3007 | 10.0 | 5900 | 1.7625 | 0.6725 |
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+ | 1.2049 | 11.0 | 6490 | 1.0667 | 0.7070 |
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+ | 1.1087 | 12.0 | 7080 | 0.9915 | 0.7156 |
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+ | 1.1023 | 13.0 | 7670 | 1.0683 | 0.6924 |
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+ | 1.0404 | 14.0 | 8260 | 1.1711 | 0.7248 |
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+ | 1.0287 | 15.0 | 8850 | 1.0966 | 0.7297 |
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+ | 0.9405 | 16.0 | 9440 | 0.9352 | 0.7107 |
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+ | 0.8558 | 17.0 | 10030 | 0.9269 | 0.7205 |
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+ | 0.8273 | 18.0 | 10620 | 0.9574 | 0.7235 |
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+ | 0.7798 | 19.0 | 11210 | 0.9598 | 0.7385 |
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+ | 0.7646 | 20.0 | 11800 | 0.9004 | 0.7287 |
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+ | 0.7505 | 21.0 | 12390 | 0.9389 | 0.7174 |
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+ | 0.7273 | 22.0 | 12980 | 0.9234 | 0.7358 |
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+ | 0.6971 | 23.0 | 13570 | 0.9055 | 0.7315 |
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+ | 0.6815 | 24.0 | 14160 | 0.8711 | 0.7352 |
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+ | 0.6729 | 25.0 | 14750 | 1.0923 | 0.7437 |
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+ | 0.6151 | 26.0 | 15340 | 0.8950 | 0.7254 |
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+ | 0.6291 | 27.0 | 15930 | 1.1086 | 0.6945 |
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+ | 0.6243 | 28.0 | 16520 | 0.9179 | 0.7410 |
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+ | 0.609 | 29.0 | 17110 | 1.0778 | 0.7410 |
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+ | 0.5733 | 30.0 | 17700 | 0.9548 | 0.7422 |
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+ | 0.5742 | 31.0 | 18290 | 1.1436 | 0.7413 |
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+ | 0.5675 | 32.0 | 18880 | 0.8956 | 0.7450 |
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+ | 0.5578 | 33.0 | 19470 | 0.9040 | 0.7382 |
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+ | 0.5339 | 34.0 | 20060 | 0.8730 | 0.7453 |
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+ | 0.5284 | 35.0 | 20650 | 1.0258 | 0.7486 |
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+ | 0.5116 | 36.0 | 21240 | 1.2775 | 0.7382 |
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+ | 0.5215 | 37.0 | 21830 | 0.9275 | 0.7477 |
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+ | 0.5038 | 38.0 | 22420 | 0.8780 | 0.7394 |
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+ | 0.5073 | 39.0 | 23010 | 0.9095 | 0.7468 |
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+ | 0.4897 | 40.0 | 23600 | 0.8864 | 0.7410 |
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+ | 0.4927 | 41.0 | 24190 | 1.1312 | 0.7391 |
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+ | 0.4941 | 42.0 | 24780 | 0.8809 | 0.7339 |
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+ | 0.4629 | 43.0 | 25370 | 1.1564 | 0.7419 |
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+ | 0.4754 | 44.0 | 25960 | 0.9223 | 0.7413 |
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+ | 0.457 | 45.0 | 26550 | 0.8677 | 0.7422 |
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+ | 0.4398 | 46.0 | 27140 | 1.0571 | 0.7471 |
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+ | 0.4612 | 47.0 | 27730 | 0.8773 | 0.7401 |
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+ | 0.4464 | 48.0 | 28320 | 0.9260 | 0.7477 |
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+ | 0.4779 | 49.0 | 28910 | 0.8712 | 0.7425 |
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+ | 0.443 | 50.0 | 29500 | 0.8886 | 0.7413 |
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+ | 0.4445 | 51.0 | 30090 | 0.8968 | 0.7431 |
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+ | 0.4274 | 52.0 | 30680 | 0.9516 | 0.7495 |
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+ | 0.4239 | 53.0 | 31270 | 0.8773 | 0.7443 |
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+ | 0.4143 | 54.0 | 31860 | 1.0295 | 0.7401 |
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+ | 0.4359 | 55.0 | 32450 | 0.8879 | 0.7453 |
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+ | 0.4197 | 56.0 | 33040 | 0.8712 | 0.7489 |
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+ | 0.397 | 57.0 | 33630 | 1.0037 | 0.7544 |
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+ | 0.402 | 58.0 | 34220 | 0.8789 | 0.7554 |
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+ | 0.4015 | 59.0 | 34810 | 0.8532 | 0.7523 |
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+ | 0.4008 | 60.0 | 35400 | 0.8840 | 0.7523 |
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+ | 0.3943 | 61.0 | 35990 | 0.9475 | 0.7462 |
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+ | 0.3968 | 62.0 | 36580 | 0.9413 | 0.7465 |
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+ | 0.394 | 63.0 | 37170 | 0.8878 | 0.7480 |
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+ | 0.3914 | 64.0 | 37760 | 0.8737 | 0.7511 |
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+ | 0.3959 | 65.0 | 38350 | 0.8553 | 0.7486 |
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+ | 0.3881 | 66.0 | 38940 | 0.8905 | 0.7495 |
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+ | 0.379 | 67.0 | 39530 | 0.8956 | 0.7489 |
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+ | 0.3821 | 68.0 | 40120 | 0.8711 | 0.7514 |
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+ | 0.3764 | 69.0 | 40710 | 0.9552 | 0.7557 |
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+ | 0.3841 | 70.0 | 41300 | 0.9638 | 0.7523 |
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+ | 0.3758 | 71.0 | 41890 | 0.8728 | 0.7453 |
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+ | 0.376 | 72.0 | 42480 | 0.9654 | 0.7450 |
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+ | 0.364 | 73.0 | 43070 | 1.0121 | 0.7477 |
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+ | 0.3567 | 74.0 | 43660 | 1.0070 | 0.7508 |
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+ | 0.3723 | 75.0 | 44250 | 0.9271 | 0.7508 |
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+ | 0.3673 | 76.0 | 44840 | 0.8824 | 0.7450 |
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+ | 0.3656 | 77.0 | 45430 | 0.8812 | 0.7477 |
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+ | 0.3722 | 78.0 | 46020 | 0.8728 | 0.7502 |
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+ | 0.3719 | 79.0 | 46610 | 0.8551 | 0.7465 |
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+ | 0.3502 | 80.0 | 47200 | 0.8913 | 0.7523 |
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+ | 0.3467 | 81.0 | 47790 | 0.8476 | 0.7489 |
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+ | 0.348 | 82.0 | 48380 | 0.8885 | 0.7517 |
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+ | 0.3498 | 83.0 | 48970 | 0.8690 | 0.7443 |
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+ | 0.3457 | 84.0 | 49560 | 0.8824 | 0.7480 |
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+ | 0.3463 | 85.0 | 50150 | 0.8450 | 0.7453 |
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+ | 0.3465 | 86.0 | 50740 | 0.8760 | 0.7459 |
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+ | 0.3418 | 87.0 | 51330 | 0.8702 | 0.7437 |
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+ | 0.3394 | 88.0 | 51920 | 0.8782 | 0.7434 |
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+ | 0.3371 | 89.0 | 52510 | 0.8950 | 0.7474 |
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+ | 0.3309 | 90.0 | 53100 | 0.8568 | 0.7398 |
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+ | 0.3321 | 91.0 | 53690 | 0.8973 | 0.7495 |
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+ | 0.3385 | 92.0 | 54280 | 0.8401 | 0.7431 |
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+ | 0.3264 | 93.0 | 54870 | 0.8658 | 0.7462 |
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+ | 0.3382 | 94.0 | 55460 | 0.8652 | 0.7483 |
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+ | 0.3279 | 95.0 | 56050 | 0.8785 | 0.7465 |
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+ | 0.3274 | 96.0 | 56640 | 0.8666 | 0.7477 |
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+ | 0.3272 | 97.0 | 57230 | 0.8666 | 0.7489 |
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+ | 0.3147 | 98.0 | 57820 | 0.8641 | 0.7498 |
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+ | 0.3172 | 99.0 | 58410 | 0.8616 | 0.7486 |
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+ | 0.3256 | 100.0 | 59000 | 0.8603 | 0.7489 |
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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