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Onutoa
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1_5e-3_10_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_5e-3_10_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_5e-3_10_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: 0.9119
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+ - Accuracy: 0.7446
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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: 0.005
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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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+ | 2.6814 | 1.0 | 590 | 2.2524 | 0.6128 |
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+ | 2.6474 | 2.0 | 1180 | 2.2889 | 0.6217 |
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+ | 2.7373 | 3.0 | 1770 | 3.8911 | 0.4401 |
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+ | 2.7048 | 4.0 | 2360 | 2.6859 | 0.6214 |
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+ | 2.3193 | 5.0 | 2950 | 3.0408 | 0.6217 |
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+ | 2.0191 | 6.0 | 3540 | 2.0926 | 0.5706 |
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+ | 1.9595 | 7.0 | 4130 | 1.7082 | 0.6908 |
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+ | 1.833 | 8.0 | 4720 | 1.7816 | 0.6092 |
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+ | 1.7395 | 9.0 | 5310 | 1.6251 | 0.6281 |
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+ | 1.7038 | 10.0 | 5900 | 2.6889 | 0.6554 |
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+ | 1.7975 | 11.0 | 6490 | 1.5326 | 0.6994 |
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+ | 1.5534 | 12.0 | 7080 | 2.6513 | 0.5554 |
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+ | 1.5833 | 13.0 | 7670 | 1.5617 | 0.6410 |
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+ | 1.4585 | 14.0 | 8260 | 1.8289 | 0.6171 |
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+ | 1.4375 | 15.0 | 8850 | 1.6306 | 0.6517 |
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+ | 1.3418 | 16.0 | 9440 | 1.2628 | 0.7153 |
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+ | 1.2576 | 17.0 | 10030 | 1.4116 | 0.7098 |
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+ | 1.2068 | 18.0 | 10620 | 1.1643 | 0.7089 |
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+ | 1.1781 | 19.0 | 11210 | 1.4702 | 0.7083 |
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+ | 1.1497 | 20.0 | 11800 | 1.1550 | 0.6988 |
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+ | 1.0552 | 21.0 | 12390 | 1.0861 | 0.7284 |
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+ | 1.047 | 22.0 | 12980 | 1.0821 | 0.7205 |
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+ | 1.0036 | 23.0 | 13570 | 1.1193 | 0.7193 |
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+ | 0.9589 | 24.0 | 14160 | 1.3591 | 0.7135 |
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+ | 0.9604 | 25.0 | 14750 | 1.0030 | 0.7229 |
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+ | 0.9283 | 26.0 | 15340 | 1.1469 | 0.7031 |
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+ | 0.9242 | 27.0 | 15930 | 1.0466 | 0.7318 |
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+ | 0.8703 | 28.0 | 16520 | 1.0736 | 0.7343 |
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+ | 0.858 | 29.0 | 17110 | 1.0357 | 0.7183 |
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+ | 0.8267 | 30.0 | 17700 | 0.9936 | 0.7339 |
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+ | 0.8148 | 31.0 | 18290 | 0.9989 | 0.7321 |
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+ | 0.7981 | 32.0 | 18880 | 1.0559 | 0.7404 |
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+ | 0.7956 | 33.0 | 19470 | 1.0207 | 0.7217 |
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+ | 0.7817 | 34.0 | 20060 | 0.9636 | 0.7361 |
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+ | 0.7545 | 35.0 | 20650 | 0.9415 | 0.7324 |
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+ | 0.7372 | 36.0 | 21240 | 1.0793 | 0.7413 |
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+ | 0.7317 | 37.0 | 21830 | 1.2911 | 0.7315 |
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+ | 0.7411 | 38.0 | 22420 | 0.9517 | 0.7364 |
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+ | 0.7093 | 39.0 | 23010 | 1.0133 | 0.7382 |
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+ | 0.6838 | 40.0 | 23600 | 1.1835 | 0.7401 |
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+ | 0.6773 | 41.0 | 24190 | 0.9180 | 0.7379 |
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+ | 0.6776 | 42.0 | 24780 | 0.9410 | 0.7367 |
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+ | 0.6486 | 43.0 | 25370 | 0.9836 | 0.7419 |
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+ | 0.6527 | 44.0 | 25960 | 0.9721 | 0.7309 |
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+ | 0.6465 | 45.0 | 26550 | 0.9508 | 0.7388 |
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+ | 0.6245 | 46.0 | 27140 | 0.9273 | 0.7434 |
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+ | 0.6258 | 47.0 | 27730 | 0.9763 | 0.7330 |
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+ | 0.6086 | 48.0 | 28320 | 0.9135 | 0.7388 |
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+ | 0.6417 | 49.0 | 28910 | 1.0037 | 0.7446 |
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+ | 0.6064 | 50.0 | 29500 | 0.9751 | 0.7398 |
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+ | 0.5938 | 51.0 | 30090 | 0.9801 | 0.7453 |
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+ | 0.5951 | 52.0 | 30680 | 0.9515 | 0.7370 |
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+ | 0.5718 | 53.0 | 31270 | 0.9160 | 0.7419 |
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+ | 0.5751 | 54.0 | 31860 | 0.9263 | 0.7462 |
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+ | 0.5839 | 55.0 | 32450 | 0.9170 | 0.7376 |
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+ | 0.5707 | 56.0 | 33040 | 0.9787 | 0.7431 |
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+ | 0.564 | 57.0 | 33630 | 0.9822 | 0.7431 |
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+ | 0.5539 | 58.0 | 34220 | 0.9335 | 0.7407 |
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+ | 0.5567 | 59.0 | 34810 | 1.0004 | 0.7370 |
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+ | 0.5555 | 60.0 | 35400 | 0.9554 | 0.7446 |
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+ | 0.5344 | 61.0 | 35990 | 0.9199 | 0.7483 |
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+ | 0.5494 | 62.0 | 36580 | 0.9970 | 0.7456 |
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+ | 0.5226 | 63.0 | 37170 | 0.9454 | 0.7434 |
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+ | 0.5275 | 64.0 | 37760 | 0.9771 | 0.7361 |
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+ | 0.5186 | 65.0 | 38350 | 1.0032 | 0.7517 |
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+ | 0.52 | 66.0 | 38940 | 0.9263 | 0.7440 |
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+ | 0.5209 | 67.0 | 39530 | 1.0130 | 0.7443 |
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+ | 0.528 | 68.0 | 40120 | 0.9466 | 0.7422 |
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+ | 0.5146 | 69.0 | 40710 | 0.9790 | 0.7456 |
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+ | 0.5026 | 70.0 | 41300 | 0.9880 | 0.7489 |
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+ | 0.5204 | 71.0 | 41890 | 0.9132 | 0.7373 |
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+ | 0.5049 | 72.0 | 42480 | 0.9589 | 0.7480 |
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+ | 0.4969 | 73.0 | 43070 | 0.9564 | 0.7446 |
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+ | 0.4911 | 74.0 | 43660 | 0.9255 | 0.7336 |
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+ | 0.4961 | 75.0 | 44250 | 0.9983 | 0.7502 |
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+ | 0.4986 | 76.0 | 44840 | 0.9003 | 0.7376 |
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+ | 0.4979 | 77.0 | 45430 | 0.8937 | 0.7385 |
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+ | 0.4941 | 78.0 | 46020 | 0.9082 | 0.7422 |
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+ | 0.487 | 79.0 | 46610 | 0.9231 | 0.7471 |
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+ | 0.4773 | 80.0 | 47200 | 0.9673 | 0.7437 |
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+ | 0.4665 | 81.0 | 47790 | 0.9598 | 0.7462 |
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+ | 0.4824 | 82.0 | 48380 | 0.9110 | 0.7410 |
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+ | 0.4795 | 83.0 | 48970 | 0.9222 | 0.7425 |
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+ | 0.4654 | 84.0 | 49560 | 0.9369 | 0.7459 |
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+ | 0.4605 | 85.0 | 50150 | 0.9379 | 0.7502 |
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+ | 0.477 | 86.0 | 50740 | 0.8911 | 0.7437 |
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+ | 0.4644 | 87.0 | 51330 | 0.9287 | 0.7434 |
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+ | 0.4539 | 88.0 | 51920 | 0.9421 | 0.7422 |
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+ | 0.4582 | 89.0 | 52510 | 0.9248 | 0.7437 |
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+ | 0.4488 | 90.0 | 53100 | 0.9152 | 0.7425 |
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+ | 0.4554 | 91.0 | 53690 | 0.9511 | 0.7471 |
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+ | 0.4547 | 92.0 | 54280 | 0.9064 | 0.7419 |
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+ | 0.4534 | 93.0 | 54870 | 0.9404 | 0.7471 |
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+ | 0.463 | 94.0 | 55460 | 0.9346 | 0.7453 |
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+ | 0.4482 | 95.0 | 56050 | 0.9191 | 0.7437 |
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+ | 0.4518 | 96.0 | 56640 | 0.9154 | 0.7431 |
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+ | 0.4326 | 97.0 | 57230 | 0.9055 | 0.7440 |
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+ | 0.4291 | 98.0 | 57820 | 0.9072 | 0.7437 |
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+ | 0.4278 | 99.0 | 58410 | 0.9101 | 0.7437 |
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+ | 0.4397 | 100.0 | 59000 | 0.9119 | 0.7446 |
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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