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finetuned-marktextepoch-n600

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update model card README.md

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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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+ model-index:
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+ - name: finetuned-marktextepoch-n600
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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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+ # finetuned-marktextepoch-n600
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+
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+ This model is a fine-tuned version of [leokai/finetuned-marktextepoch-n500](https://huggingface.co/leokai/finetuned-marktextepoch-n500) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 2.6814
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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: 2e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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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: 182
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:------:|:---------------:|
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+ | 0.5332 | 1.0 | 1606 | 2.5256 |
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+ | 0.5315 | 2.0 | 3212 | 2.4835 |
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+ | 0.5181 | 3.0 | 4818 | 2.5471 |
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+ | 0.5318 | 4.0 | 6424 | 2.5213 |
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+ | 0.5398 | 5.0 | 8030 | 2.5408 |
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+ | 0.5474 | 6.0 | 9636 | 2.5557 |
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+ | 0.541 | 7.0 | 11242 | 2.5415 |
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+ | 0.529 | 8.0 | 12848 | 2.5729 |
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+ | 0.5294 | 9.0 | 14454 | 2.5533 |
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+ | 0.5404 | 10.0 | 16060 | 2.5414 |
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+ | 0.5359 | 11.0 | 17666 | 2.5316 |
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+ | 0.5295 | 12.0 | 19272 | 2.5985 |
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+ | 0.5319 | 13.0 | 20878 | 2.5644 |
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+ | 0.5492 | 14.0 | 22484 | 2.5594 |
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+ | 0.5403 | 15.0 | 24090 | 2.5830 |
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+ | 0.526 | 16.0 | 25696 | 2.5999 |
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+ | 0.5308 | 17.0 | 27302 | 2.5629 |
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+ | 0.516 | 18.0 | 28908 | 2.6015 |
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+ | 0.525 | 19.0 | 30514 | 2.5726 |
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+ | 0.5238 | 20.0 | 32120 | 2.5656 |
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+ | 0.5244 | 21.0 | 33726 | 2.5961 |
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+ | 0.531 | 22.0 | 35332 | 2.5809 |
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+ | 0.517 | 23.0 | 36938 | 2.5688 |
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+ | 0.5334 | 24.0 | 38544 | 2.5828 |
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+ | 0.505 | 25.0 | 40150 | 2.5861 |
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+ | 0.5136 | 26.0 | 41756 | 2.6044 |
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+ | 0.5228 | 27.0 | 43362 | 2.6000 |
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+ | 0.5066 | 28.0 | 44968 | 2.5971 |
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+ | 0.5183 | 29.0 | 46574 | 2.6240 |
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+ | 0.5076 | 30.0 | 48180 | 2.6201 |
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+ | 0.5059 | 31.0 | 49786 | 2.5746 |
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+ | 0.5033 | 32.0 | 51392 | 2.6229 |
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+ | 0.5041 | 33.0 | 52998 | 2.6086 |
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+ | 0.5132 | 34.0 | 54604 | 2.6115 |
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+ | 0.5007 | 35.0 | 56210 | 2.5865 |
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+ | 0.4947 | 36.0 | 57816 | 2.6159 |
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+ | 0.4997 | 37.0 | 59422 | 2.6072 |
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+ | 0.4988 | 38.0 | 61028 | 2.5931 |
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+ | 0.5001 | 39.0 | 62634 | 2.5956 |
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+ | 0.5027 | 40.0 | 64240 | 2.6444 |
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+ | 0.4969 | 41.0 | 65846 | 2.6194 |
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+ | 0.4916 | 42.0 | 67452 | 2.6394 |
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+ | 0.4986 | 43.0 | 69058 | 2.6401 |
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+ | 0.5 | 44.0 | 70664 | 2.6164 |
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+ | 0.4848 | 45.0 | 72270 | 2.6479 |
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+ | 0.4926 | 46.0 | 73876 | 2.6519 |
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+ | 0.492 | 47.0 | 75482 | 2.6359 |
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+ | 0.4939 | 48.0 | 77088 | 2.6211 |
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+ | 0.4914 | 49.0 | 78694 | 2.6536 |
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+ | 0.4743 | 50.0 | 80300 | 2.6434 |
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+ | 0.4787 | 51.0 | 81906 | 2.6396 |
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+ | 0.4686 | 52.0 | 83512 | 2.6337 |
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+ | 0.4775 | 53.0 | 85118 | 2.6352 |
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+ | 0.4844 | 54.0 | 86724 | 2.6382 |
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+ | 0.4802 | 55.0 | 88330 | 2.6473 |
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+ | 0.4799 | 56.0 | 89936 | 2.6284 |
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+ | 0.4749 | 57.0 | 91542 | 2.6371 |
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+ | 0.4779 | 58.0 | 93148 | 2.6264 |
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+ | 0.4727 | 59.0 | 94754 | 2.6506 |
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+ | 0.4875 | 60.0 | 96360 | 2.6677 |
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+ | 0.4695 | 61.0 | 97966 | 2.6507 |
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+ | 0.4612 | 62.0 | 99572 | 2.6600 |
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+ | 0.4658 | 63.0 | 101178 | 2.6442 |
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+ | 0.4737 | 64.0 | 102784 | 2.6593 |
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+ | 0.47 | 65.0 | 104390 | 2.6451 |
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+ | 0.4658 | 66.0 | 105996 | 2.6493 |
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+ | 0.4634 | 67.0 | 107602 | 2.6795 |
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+ | 0.4713 | 68.0 | 109208 | 2.6392 |
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+ | 0.4771 | 69.0 | 110814 | 2.6633 |
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+ | 0.4704 | 70.0 | 112420 | 2.6273 |
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+ | 0.458 | 71.0 | 114026 | 2.6426 |
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+ | 0.4577 | 72.0 | 115632 | 2.6652 |
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+ | 0.4585 | 73.0 | 117238 | 2.6609 |
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+ | 0.4567 | 74.0 | 118844 | 2.6285 |
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+ | 0.4524 | 75.0 | 120450 | 2.6860 |
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+ | 0.4615 | 76.0 | 122056 | 2.7033 |
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+ | 0.4725 | 77.0 | 123662 | 2.6877 |
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+ | 0.4621 | 78.0 | 125268 | 2.6343 |
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+ | 0.4555 | 79.0 | 126874 | 2.6664 |
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+ | 0.4485 | 80.0 | 128480 | 2.6650 |
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+ | 0.4508 | 81.0 | 130086 | 2.6777 |
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+ | 0.4475 | 82.0 | 131692 | 2.6759 |
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+ | 0.4432 | 83.0 | 133298 | 2.6711 |
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+ | 0.4541 | 84.0 | 134904 | 2.6905 |
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+ | 0.444 | 85.0 | 136510 | 2.6699 |
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+ | 0.4428 | 86.0 | 138116 | 2.6737 |
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+ | 0.4436 | 87.0 | 139722 | 2.6536 |
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+ | 0.4522 | 88.0 | 141328 | 2.6504 |
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+ | 0.4632 | 89.0 | 142934 | 2.6697 |
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+ | 0.4514 | 90.0 | 144540 | 2.6854 |
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+ | 0.4369 | 91.0 | 146146 | 2.6804 |
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+ | 0.4324 | 92.0 | 147752 | 2.7011 |
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+ | 0.4436 | 93.0 | 149358 | 2.7145 |
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+ | 0.4317 | 94.0 | 150964 | 2.6880 |
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+ | 0.4468 | 95.0 | 152570 | 2.6784 |
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+ | 0.4364 | 96.0 | 154176 | 2.7050 |
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+ | 0.4505 | 97.0 | 155782 | 2.7214 |
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+ | 0.4273 | 98.0 | 157388 | 2.6843 |
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+ | 0.4374 | 99.0 | 158994 | 2.7047 |
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+ | 0.4436 | 100.0 | 160600 | 2.6934 |
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+ | 0.4399 | 101.0 | 162206 | 2.6913 |
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+ | 0.4273 | 102.0 | 163812 | 2.6949 |
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+ | 0.4334 | 103.0 | 165418 | 2.6628 |
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+ | 0.4277 | 104.0 | 167024 | 2.7170 |
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+ | 0.439 | 105.0 | 168630 | 2.6752 |
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+ | 0.4418 | 106.0 | 170236 | 2.6832 |
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+ | 0.4278 | 107.0 | 171842 | 2.6386 |
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+ | 0.4226 | 108.0 | 173448 | 2.6946 |
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+ | 0.4255 | 109.0 | 175054 | 2.6911 |
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+ | 0.4349 | 110.0 | 176660 | 2.7073 |
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+ | 0.4259 | 111.0 | 178266 | 2.7048 |
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+ | 0.4328 | 112.0 | 179872 | 2.7105 |
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+ | 0.4242 | 113.0 | 181478 | 2.6897 |
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+ | 0.4228 | 114.0 | 183084 | 2.6921 |
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+ | 0.4227 | 115.0 | 184690 | 2.6833 |
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+ | 0.4192 | 116.0 | 186296 | 2.6483 |
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+ | 0.4381 | 117.0 | 187902 | 2.6690 |
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+ | 0.425 | 118.0 | 189508 | 2.6866 |
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+ | 0.4273 | 119.0 | 191114 | 2.6892 |
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+ | 0.4201 | 120.0 | 192720 | 2.7128 |
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+ | 0.4252 | 121.0 | 194326 | 2.6883 |
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+ | 0.423 | 122.0 | 195932 | 2.6766 |
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+ | 0.4371 | 123.0 | 197538 | 2.7092 |
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+ | 0.4363 | 124.0 | 199144 | 2.7084 |
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+ | 0.4315 | 125.0 | 200750 | 2.7321 |
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+ | 0.4367 | 126.0 | 202356 | 2.7005 |
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+ | 0.4114 | 127.0 | 203962 | 2.6878 |
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+ | 0.4025 | 128.0 | 205568 | 2.7100 |
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+ | 0.4376 | 129.0 | 207174 | 2.7073 |
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+ | 0.4201 | 130.0 | 208780 | 2.7064 |
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+ | 0.4248 | 131.0 | 210386 | 2.6755 |
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+ | 0.4333 | 132.0 | 211992 | 2.6884 |
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+ | 0.4178 | 133.0 | 213598 | 2.6688 |
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+ | 0.433 | 134.0 | 215204 | 2.6911 |
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+ | 0.4145 | 135.0 | 216810 | 2.7116 |
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+ | 0.4163 | 136.0 | 218416 | 2.6867 |
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+ | 0.4203 | 137.0 | 220022 | 2.7109 |
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+ | 0.4164 | 138.0 | 221628 | 2.7031 |
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+ | 0.4252 | 139.0 | 223234 | 2.6656 |
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+ | 0.4302 | 140.0 | 224840 | 2.7018 |
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+ | 0.4205 | 141.0 | 226446 | 2.6912 |
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+ | 0.4055 | 142.0 | 228052 | 2.7107 |
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+ | 0.4204 | 143.0 | 229658 | 2.7236 |
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+ | 0.4104 | 144.0 | 231264 | 2.6931 |
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+ | 0.4146 | 145.0 | 232870 | 2.7160 |
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+ | 0.4113 | 146.0 | 234476 | 2.7116 |
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+ | 0.4375 | 147.0 | 236082 | 2.6680 |
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+ | 0.4135 | 148.0 | 237688 | 2.6984 |
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+ | 0.4198 | 149.0 | 239294 | 2.6823 |
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+ | 0.4154 | 150.0 | 240900 | 2.7031 |
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+ | 0.4159 | 151.0 | 242506 | 2.7000 |
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+ | 0.4104 | 152.0 | 244112 | 2.6974 |
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+ | 0.4283 | 153.0 | 245718 | 2.6649 |
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+ | 0.4046 | 154.0 | 247324 | 2.6989 |
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+ | 0.4174 | 155.0 | 248930 | 2.6774 |
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+ | 0.4199 | 156.0 | 250536 | 2.6943 |
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+ | 0.421 | 157.0 | 252142 | 2.6728 |
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+ | 0.4106 | 158.0 | 253748 | 2.6836 |
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+ | 0.4081 | 159.0 | 255354 | 2.6946 |
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+ | 0.4233 | 160.0 | 256960 | 2.6992 |
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+ | 0.4183 | 161.0 | 258566 | 2.6585 |
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+ | 0.4213 | 162.0 | 260172 | 2.6761 |
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+ | 0.4259 | 163.0 | 261778 | 2.7186 |
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+ | 0.4157 | 164.0 | 263384 | 2.7150 |
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+ | 0.4257 | 165.0 | 264990 | 2.7004 |
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+ | 0.4251 | 166.0 | 266596 | 2.6728 |
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+ | 0.4228 | 167.0 | 268202 | 2.6831 |
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+ | 0.4233 | 168.0 | 269808 | 2.6781 |
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+ | 0.418 | 169.0 | 271414 | 2.6598 |
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+ | 0.4263 | 170.0 | 273020 | 2.6930 |
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+ | 0.4104 | 171.0 | 274626 | 2.7045 |
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+ | 0.4213 | 172.0 | 276232 | 2.6979 |
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+ | 0.419 | 173.0 | 277838 | 2.6726 |
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+ | 0.4273 | 174.0 | 279444 | 2.6631 |
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+ | 0.4189 | 175.0 | 281050 | 2.6802 |
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+ | 0.4228 | 176.0 | 282656 | 2.6872 |
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+ | 0.431 | 177.0 | 284262 | 2.6677 |
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+ | 0.4363 | 178.0 | 285868 | 2.6710 |
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+ | 0.4145 | 179.0 | 287474 | 2.6654 |
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+ | 0.4256 | 180.0 | 289080 | 2.6802 |
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+ | 0.4277 | 181.0 | 290686 | 2.6698 |
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+ | 0.4249 | 182.0 | 292292 | 2.6814 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.21.1
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+ - Pytorch 1.12.0+cu113
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+ - Datasets 2.4.0
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+ - Tokenizers 0.12.1