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lge_tests_prelim

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Safetensors
nanogpt
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  1. README.md +34 -81
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -16,8 +16,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4744
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- - Accuracy: 0.155
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  ## Model description
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@@ -49,85 +49,38 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|
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- | No log | 0 | 0 | 2.6240 | 0.0 |
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- | 2.5537 | 0.0128 | 100 | 2.5486 | 0.0 |
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- | 2.441 | 0.0256 | 200 | 2.4292 | 0.0 |
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- | 2.3334 | 0.0384 | 300 | 2.3352 | 0.0 |
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- | 2.2591 | 0.0512 | 400 | 2.2684 | 0.0 |
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- | 2.1684 | 0.0640 | 500 | 2.1689 | 0.0 |
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- | 2.0283 | 0.0768 | 600 | 2.0548 | 0.0 |
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- | 1.8348 | 0.0896 | 700 | 1.8243 | 0.0 |
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- | 1.6261 | 0.1024 | 800 | 1.6267 | 0.0 |
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- | 1.4689 | 0.1152 | 900 | 1.6175 | 0.0 |
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- | 1.3403 | 0.1280 | 1000 | 1.3556 | 0.03 |
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- | 1.2923 | 0.1408 | 1100 | 1.2588 | 0.015 |
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- | 1.2468 | 0.1536 | 1200 | 1.1891 | 0.01 |
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- | 1.1383 | 0.1665 | 1300 | 1.1733 | 0.0 |
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- | 1.0702 | 0.1793 | 1400 | 1.0517 | 0.03 |
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- | 1.129 | 0.1921 | 1500 | 1.0673 | 0.015 |
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- | 1.0237 | 0.2049 | 1600 | 0.9700 | 0.035 |
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- | 1.0182 | 0.2177 | 1700 | 0.9626 | 0.06 |
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- | 0.8731 | 0.2305 | 1800 | 0.8745 | 0.04 |
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- | 0.8311 | 0.2433 | 1900 | 0.8513 | 0.035 |
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- | 0.8283 | 0.2561 | 2000 | 0.8341 | 0.055 |
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- | 0.8011 | 0.2689 | 2100 | 0.7890 | 0.045 |
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- | 0.7876 | 0.2817 | 2200 | 0.7937 | 0.075 |
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- | 0.7777 | 0.2945 | 2300 | 0.7606 | 0.04 |
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- | 0.7303 | 0.3073 | 2400 | 0.7596 | 0.05 |
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- | 0.7163 | 0.3201 | 2500 | 0.7237 | 0.085 |
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- | 0.7332 | 0.3329 | 2600 | 0.7103 | 0.055 |
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- | 0.7387 | 0.3457 | 2700 | 0.6866 | 0.04 |
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- | 0.7272 | 0.3585 | 2800 | 0.7362 | 0.11 |
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- | 0.6552 | 0.3713 | 2900 | 0.6453 | 0.1 |
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- | 0.6139 | 0.3841 | 3000 | 0.6549 | 0.05 |
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- | 0.678 | 0.3969 | 3100 | 0.6556 | 0.11 |
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- | 0.6676 | 0.4097 | 3200 | 0.6356 | 0.085 |
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- | 0.5929 | 0.4225 | 3300 | 0.6442 | 0.16 |
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- | 0.6222 | 0.4353 | 3400 | 0.6219 | 0.125 |
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- | 0.6353 | 0.4481 | 3500 | 0.7022 | 0.115 |
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- | 0.6162 | 0.4609 | 3600 | 0.6556 | 0.13 |
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- | 0.5968 | 0.4738 | 3700 | 0.5898 | 0.075 |
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- | 0.6839 | 0.4866 | 3800 | 0.6464 | 0.09 |
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- | 0.574 | 0.4994 | 3900 | 0.5832 | 0.065 |
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- | 0.5742 | 0.5122 | 4000 | 0.5742 | 0.1 |
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- | 0.5895 | 0.5250 | 4100 | 0.6034 | 0.06 |
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- | 0.5903 | 0.5378 | 4200 | 0.6171 | 0.065 |
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- | 0.5645 | 0.5506 | 4300 | 0.5875 | 0.13 |
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- | 0.5327 | 0.5634 | 4400 | 0.5438 | 0.08 |
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- | 0.5757 | 0.5762 | 4500 | 0.5725 | 0.08 |
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- | 0.5848 | 0.5890 | 4600 | 0.5414 | 0.145 |
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- | 0.5408 | 0.6018 | 4700 | 0.5364 | 0.1 |
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- | 0.6447 | 0.6146 | 4800 | 0.5806 | 0.105 |
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- | 0.5924 | 0.6274 | 4900 | 0.5655 | 0.1 |
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- | 0.5311 | 0.6402 | 5000 | 0.5731 | 0.095 |
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- | 0.511 | 0.6530 | 5100 | 0.5145 | 0.095 |
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- | 0.5064 | 0.6658 | 5200 | 0.5349 | 0.115 |
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- | 0.5124 | 0.6786 | 5300 | 0.5246 | 0.09 |
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- | 0.4798 | 0.6914 | 5400 | 0.5063 | 0.11 |
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- | 0.5151 | 0.7042 | 5500 | 0.5641 | 0.175 |
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- | 0.5295 | 0.7170 | 5600 | 0.5029 | 0.125 |
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- | 0.5365 | 0.7298 | 5700 | 0.5093 | 0.09 |
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- | 0.5376 | 0.7426 | 5800 | 0.4999 | 0.15 |
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- | 0.4899 | 0.7554 | 5900 | 0.4972 | 0.155 |
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- | 0.4869 | 0.7682 | 6000 | 0.4914 | 0.11 |
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- | 0.5017 | 0.7810 | 6100 | 0.4947 | 0.165 |
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- | 0.4785 | 0.7939 | 6200 | 0.4999 | 0.12 |
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- | 0.4759 | 0.8067 | 6300 | 0.4922 | 0.12 |
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- | 0.476 | 0.8195 | 6400 | 0.4888 | 0.12 |
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- | 0.465 | 0.8323 | 6500 | 0.4846 | 0.14 |
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- | 0.4904 | 0.8451 | 6600 | 0.4829 | 0.145 |
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- | 0.4747 | 0.8579 | 6700 | 0.4859 | 0.145 |
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- | 0.4777 | 0.8707 | 6800 | 0.4821 | 0.185 |
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- | 0.5079 | 0.8835 | 6900 | 0.4766 | 0.14 |
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- | 0.4783 | 0.8963 | 7000 | 0.4809 | 0.13 |
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- | 0.4786 | 0.9091 | 7100 | 0.4821 | 0.09 |
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- | 0.48 | 0.9219 | 7200 | 0.4776 | 0.15 |
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- | 0.4804 | 0.9347 | 7300 | 0.4792 | 0.17 |
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- | 0.481 | 0.9475 | 7400 | 0.4753 | 0.15 |
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- | 0.4904 | 0.9603 | 7500 | 0.4757 | 0.14 |
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- | 0.4665 | 0.9731 | 7600 | 0.4752 | 0.155 |
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- | 0.4923 | 0.9859 | 7700 | 0.4745 | 0.15 |
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- | 0.4826 | 0.9987 | 7800 | 0.4744 | 0.155 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.4550
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+ - Accuracy: 0.66
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|
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+ | No log | 0 | 0 | 2.6203 | 0.0 |
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+ | 2.4848 | 0.0320 | 100 | 2.4757 | 0.0 |
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+ | 2.3355 | 0.0641 | 200 | 2.3212 | 0.0 |
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+ | 2.202 | 0.0961 | 300 | 2.2228 | 0.0 |
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+ | 2.068 | 0.1281 | 400 | 2.0466 | 0.0 |
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+ | 1.6899 | 0.1602 | 500 | 1.6584 | 0.0 |
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+ | 1.4558 | 0.1922 | 600 | 1.5536 | 0.005 |
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+ | 1.3624 | 0.2242 | 700 | 1.3155 | 0.015 |
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+ | 1.2388 | 0.2562 | 800 | 1.2468 | 0.025 |
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+ | 1.0832 | 0.2883 | 900 | 1.1109 | 0.095 |
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+ | 1.0392 | 0.3203 | 1000 | 1.0326 | 0.09 |
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+ | 0.968 | 0.3523 | 1100 | 0.9448 | 0.2 |
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+ | 0.8818 | 0.3844 | 1200 | 0.8892 | 0.205 |
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+ | 0.8384 | 0.4164 | 1300 | 0.8277 | 0.255 |
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+ | 0.7951 | 0.4484 | 1400 | 0.7869 | 0.28 |
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+ | 0.742 | 0.4805 | 1500 | 0.7629 | 0.275 |
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+ | 0.7107 | 0.5125 | 1600 | 0.7139 | 0.385 |
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+ | 0.6854 | 0.5445 | 1700 | 0.6708 | 0.41 |
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+ | 0.6381 | 0.5766 | 1800 | 0.6422 | 0.43 |
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+ | 0.6085 | 0.6086 | 1900 | 0.6061 | 0.49 |
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+ | 0.5915 | 0.6406 | 2000 | 0.5896 | 0.42 |
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+ | 0.5809 | 0.6726 | 2100 | 0.5598 | 0.53 |
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+ | 0.5303 | 0.7047 | 2200 | 0.5339 | 0.565 |
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+ | 0.5205 | 0.7367 | 2300 | 0.5170 | 0.585 |
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+ | 0.4997 | 0.7687 | 2400 | 0.5155 | 0.515 |
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+ | 0.4753 | 0.8008 | 2500 | 0.4972 | 0.55 |
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+ | 0.4797 | 0.8328 | 2600 | 0.4745 | 0.645 |
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+ | 0.4729 | 0.8648 | 2700 | 0.4737 | 0.6 |
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+ | 0.469 | 0.8969 | 2800 | 0.4661 | 0.65 |
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+ | 0.4562 | 0.9289 | 2900 | 0.4585 | 0.65 |
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+ | 0.4474 | 0.9609 | 3000 | 0.4557 | 0.64 |
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+ | 0.4462 | 0.9930 | 3100 | 0.4550 | 0.66 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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@@ -1,3 +1,3 @@
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