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hrezaei/T5La-Large
T5La-Large is a text generation model from hrezaei. Use it when you need the model to write or continue text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
Downloads · 30 days
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From the Hugging Face model README
This model is a fine-tuned version of on the HuggingFaceFW/fineweb sample-350BT dataset. It achieves the following results on the evaluation set:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 6.9745 | 0.0095 | 5000 | 6.9068 | 0.0314 |
| 6.7778 | 0.0191 | 10000 | 6.7410 | 0.0313 |
| 6.715 | 0.0286 | 15000 | 6.6431 | 0.0333 |
| 6.6547 | 0.0381 | 20000 | 6.5784 | 0.0335 |
| 6.5695 | 0.0477 | 25000 | 6.5298 | 0.0341 |
| 6.5283 | 0.0572 | 30000 | 6.5265 | 0.0340 |
| 6.5826 | 0.0668 | 35000 | 6.4902 | 0.0340 |
| 6.5631 | 0.0763 | 40000 | 6.4705 | 0.0357 |
| 6.5234 | 0.0858 | 45000 | 6.4617 | 0.0339 |
| 6.548 | 0.0954 | 50000 | 6.4475 | 0.0350 |
| 6.599 | 0.1049 | 55000 | 6.4514 | 0.0355 |
| 6.547 | 0.1144 | 60000 | 6.4568 | 0.0364 |
| 6.5265 | 0.1240 | 65000 | 6.4709 | 0.0381 |
| 6.5916 | 0.1335 | 70000 | 6.4962 | 0.0372 |
| 6.5919 | 0.1431 | 75000 | 6.4827 | 0.0375 |
| 6.4745 | 0.1526 | 80000 | 6.4902 | 0.0385 |
| 6.6695 | 0.1621 | 85000 | 6.5442 | 0.0384 |
| 6.5994 | 0.1717 | 90000 | 6.5036 | 0.0387 |
| 6.6023 | 0.1812 | 95000 | 6.4979 | 0.0385 |
| 6.5913 | 0.1907 | 100000 | 6.5830 | 0.0382 |
| 6.6542 | 0.2003 | 105000 | 6.5550 | 0.0384 |
| 6.6602 | 0.2098 | 110000 | 6.5538 | 0.0388 |
| 6.6113 | 0.2193 | 115000 | 6.5508 | 0.0393 |
| 6.6568 | 0.2289 | 120000 | 6.5527 | 0.0388 |
| 6.6476 | 0.2384 | 125000 | 6.5457 | 0.0391 |
| 6.6636 | 0.2480 | 130000 | 6.5458 | 0.0401 |
| 6.6318 | 0.2575 | 135000 | 6.5468 | 0.0399 |
| 6.6358 | 0.2670 | 140000 | 6.5729 | 0.0374 |
| 6.639 | 0.2766 | 145000 | 6.5532 | 0.0394 |
| 6.6817 | 0.2861 | 150000 | 6.5516 | 0.0391 |
| 6.6339 | 0.2956 | 155000 | 6.5509 | 0.0389 |
| 6.6132 | 0.3052 | 160000 | 6.5391 | 0.0381 |
| 6.6347 | 0.3147 | 165000 | 6.5376 | 0.0386 |
| 6.6542 | 0.3242 | 170000 | 6.5377 | 0.0397 |
| 6.619 | 0.3338 | 175000 | 6.5441 | 0.0388 |
| 6.6979 | 0.3433 | 180000 | 6.5556 | 0.0394 |
| 6.6485 | 0.3529 | 185000 | 6.5370 | 0.0399 |
| 6.6035 | 0.3624 | 190000 | 6.5300 | 0.0389 |
| 6.6574 | 0.3719 | 195000 | 6.5272 | 0.0385 |
| 6.6152 | 0.3815 | 200000 | 6.5326 | 0.0377 |
| 6.5946 | 0.3910 | 205000 | 6.5314 | 0.0386 |
| 6.6747 | 0.4005 | 210000 | 6.5184 | 0.0390 |
| 6.618 | 0.4101 | 215000 | 6.5262 | 0.0375 |
| 6.6218 | 0.4196 | 220000 | 6.5339 | 0.0388 |
| 6.6659 | 0.4292 | 225000 | 6.5258 | 0.0383 |
| 6.6292 | 0.4387 | 230000 | 6.5242 | 0.0387 |
| 6.6608 | 0.4482 | 235000 | 6.5588 | 0.0359 |
| 6.5772 | 0.4578 | 240000 | 6.5117 | 0.0389 |
| 6.5961 | 0.4673 | 245000 | 6.5381 | 0.0359 |
| 6.563 | 0.4768 | 250000 | 6.5191 | 0.0401 |
| 6.5651 | 0.4864 | 255000 | 6.4980 | 0.0385 |
| 6.5398 | 0.4959 | 260000 | 6.4998 | 0.0389 |
| 6.5368 | 0.5054 | 265000 | 6.4984 | 0.0389 |
| 6.599 | 0.5150 | 270000 | 6.4935 | 0.0388 |
| 6.6015 | 0.5245 | 275000 | 6.4891 | 0.0388 |
| 6.5597 | 0.5341 | 280000 | 6.4779 | 0.0394 |
| 6.5695 | 0.5436 | 285000 | 6.4823 | 0.0395 |
| 6.5809 | 0.5531 | 290000 | 6.4925 | 0.0382 |
| 6.6522 | 0.5627 | 295000 | 6.4898 | 0.0390 |
| 6.5688 | 0.5722 | 300000 | 6.4914 | 0.0389 |
| 6.5445 | 0.5817 | 305000 | 6.4828 | 0.0389 |
| 6.5674 | 0.5913 | 310000 | 6.4940 | 0.0388 |
| 6.5926 | 0.6008 | 315000 | 6.4786 | 0.0388 |
| 6.4979 | 0.6104 | 320000 | 6.4754 | 0.0391 |
| 6.5669 | 0.6199 | 325000 | 6.4722 | 0.0394 |
| 6.5335 | 0.6294 | 330000 | 6.4731 | 0.0398 |
| 6.5727 | 0.6390 | 335000 | 6.4770 | 0.0394 |
| 6.5735 | 0.6485 | 340000 | 6.4814 | 0.0390 |
| 6.5672 | 0.6580 | 345000 | 6.4611 | 0.0394 |
| 6.5223 | 0.6676 | 350000 | 6.4624 | 0.0397 |
| 6.518 | 0.6771 | 355000 | 6.4734 | 0.0402 |
| 6.5466 | 0.6866 | 360000 | 6.4640 | 0.0399 |
| 6.5213 | 0.6962 | 365000 | 6.4624 | 0.0401 |
| 6.5881 | 0.7057 | 370000 | 6.4505 | 0.0399 |
| 6.5353 | 0.7153 | 375000 | 6.4470 | 0.0404 |
| 6.5371 | 0.7248 | 380000 | 6.4453 | 0.0401 |
| 6.5153 | 0.7343 | 385000 | 6.4461 | 0.0401 |
| 6.5488 | 0.7439 | 390000 | 6.4434 | 0.0401 |
| 6.5121 | 0.7534 | 395000 | 6.4468 | 0.0395 |
| 6.5106 | 0.7629 | 400000 | 6.4364 | 0.0399 |
| 6.5572 | 0.7725 | 405000 | 6.4443 | 0.0405 |
| 6.494 | 0.7820 | 410000 | 6.4338 | 0.0402 |
| 6.5233 | 0.7915 | 415000 | 6.4318 | 0.0404 |
| 6.4718 | 0.8011 | 420000 | 6.4255 | 0.0415 |
| 6.4915 | 0.8106 | 425000 | 6.4261 | 0.0402 |
| 6.5007 | 0.8202 | 430000 | 6.4244 | 0.0407 |
| 6.488 | 0.8297 | 435000 | 6.4187 | 0.0405 |
| 6.5093 | 0.8392 | 440000 | 6.4163 | 0.0402 |
| 6.5029 | 0.8488 | 445000 | 6.4152 | 0.0403 |
| 6.3943 | 0.8583 | 450000 | 6.4201 | 0.0402 |
| 6.5358 | 0.8678 | 455000 | 6.4104 | 0.0410 |
| 6.5185 | 0.8774 | 460000 | 6.4099 | 0.0411 |
| 6.4622 | 0.8869 | 465000 | 6.4110 | 0.0408 |
| 6.4632 | 0.8965 | 470000 | 6.4088 | 0.0405 |
| 6.5168 | 0.9060 | 475000 | 6.4056 | 0.0408 |
| 6.4607 | 0.9155 | 480000 | 6.4000 | 0.0404 |
| 6.4444 | 0.9251 | 485000 | 6.4024 | 0.0404 |
| 6.5035 | 0.9346 | 490000 | 6.3991 | 0.0404 |
| 6.4861 | 0.9441 | 495000 | 6.3996 | 0.0407 |
| 6.4772 | 0.9537 | 500000 | 6.3965 | 0.0403 |
| 6.4699 | 1.0095 | 505000 | 6.3943 | 0.0408 |
| 6.4423 | 1.0191 | 510000 | 6.3959 | 0.0407 |
| 6.4724 | 1.0286 | 515000 | 6.3930 | 0.0410 |
| 6.4827 | 1.0381 | 520000 | 6.3910 | 0.0409 |