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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: 0.9923
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- - Accuracy: 0.01
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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 | 2.6059 | 0.0 |
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- | 1.8278 | 0.0128 | 100 | 1.7932 | 0.0 |
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- | 1.7081 | 0.0256 | 200 | 1.5708 | 0.0 |
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- | 1.6759 | 0.0384 | 300 | 1.5720 | 0.0 |
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- | 1.6075 | 0.0512 | 400 | 1.5532 | 0.0 |
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- | 1.5364 | 0.0640 | 500 | 1.5670 | 0.0 |
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- | 1.5597 | 0.0768 | 600 | 1.8279 | 0.0 |
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- | 1.563 | 0.0896 | 700 | 1.5791 | 0.0 |
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- | 1.5814 | 0.1024 | 800 | 1.5498 | 0.0 |
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- | 1.5705 | 0.1152 | 900 | 1.6980 | 0.005 |
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- | 1.6682 | 0.1280 | 1000 | 1.5166 | 0.005 |
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- | 1.5143 | 0.1408 | 1100 | 1.4964 | 0.005 |
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- | 1.6411 | 0.1536 | 1200 | 1.6380 | 0.0 |
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- | 1.4106 | 0.1665 | 1300 | 1.4373 | 0.0 |
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- | 1.4435 | 0.1793 | 1400 | 1.4208 | 0.0 |
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- | 1.3563 | 0.1921 | 1500 | 1.3553 | 0.01 |
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- | 1.5197 | 0.2049 | 1600 | 1.3802 | 0.0 |
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- | 1.3383 | 0.2177 | 1700 | 1.4022 | 0.015 |
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- | 1.4566 | 0.2305 | 1800 | 1.3946 | 0.005 |
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- | 1.4017 | 0.2433 | 1900 | 1.2900 | 0.01 |
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- | 1.3362 | 0.2561 | 2000 | 1.2311 | 0.01 |
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- | 1.3351 | 0.2689 | 2100 | 1.2454 | 0.0 |
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- | 1.2865 | 0.2817 | 2200 | 1.2590 | 0.015 |
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- | 1.2604 | 0.2945 | 2300 | 1.3772 | 0.0 |
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- | 1.1938 | 0.3073 | 2400 | 1.2460 | 0.01 |
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- | 1.2565 | 0.3201 | 2500 | 1.2472 | 0.005 |
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- | 1.2699 | 0.3329 | 2600 | 1.2403 | 0.005 |
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- | 1.2426 | 0.3457 | 2700 | 1.2033 | 0.01 |
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- | 1.2837 | 0.3585 | 2800 | 1.2875 | 0.005 |
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- | 1.1576 | 0.3713 | 2900 | 1.1139 | 0.02 |
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- | 1.0833 | 0.3841 | 3000 | 1.0916 | 0.005 |
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- | 1.5792 | 0.3969 | 3100 | 1.4673 | 0.0 |
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- | 1.126 | 0.4097 | 3200 | 1.1218 | 0.01 |
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- | 1.0863 | 0.4225 | 3300 | 1.1320 | 0.005 |
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- | 1.2114 | 0.4353 | 3400 | 1.1407 | 0.015 |
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- | 1.0692 | 0.4481 | 3500 | 1.1358 | 0.015 |
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- | 1.1152 | 0.4609 | 3600 | 1.1082 | 0.015 |
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- | 1.0694 | 0.4738 | 3700 | 1.0660 | 0.0 |
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- | 1.47 | 0.4866 | 3800 | 1.3020 | 0.01 |
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- | 1.1635 | 0.4994 | 3900 | 1.2220 | 0.015 |
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- | 1.1865 | 0.5122 | 4000 | 1.1467 | 0.015 |
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- | 1.1335 | 0.5250 | 4100 | 1.1848 | 0.005 |
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- | 1.1344 | 0.5378 | 4200 | 1.1356 | 0.005 |
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- | 1.1269 | 0.5506 | 4300 | 1.1379 | 0.02 |
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- | 1.0876 | 0.5634 | 4400 | 1.0848 | 0.0 |
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- | 1.074 | 0.5762 | 4500 | 1.0773 | 0.02 |
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- | 1.072 | 0.5890 | 4600 | 1.0582 | 0.015 |
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- | 1.0732 | 0.6018 | 4700 | 1.0603 | 0.03 |
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- | 1.0233 | 0.6146 | 4800 | 1.0335 | 0.03 |
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- | 1.0141 | 0.6274 | 4900 | 1.0213 | 0.02 |
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- | 1.0156 | 0.6402 | 5000 | 1.0254 | 0.005 |
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- | 1.0286 | 0.6530 | 5100 | 1.0372 | 0.005 |
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- | 1.0244 | 0.6658 | 5200 | 1.0199 | 0.025 |
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- | 1.0561 | 0.6786 | 5300 | 1.0206 | 0.01 |
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- | 1.0174 | 0.6914 | 5400 | 1.0212 | 0.03 |
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- | 1.027 | 0.7042 | 5500 | 1.0118 | 0.03 |
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- | 1.0238 | 0.7170 | 5600 | 1.0151 | 0.015 |
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- | 1.0486 | 0.7298 | 5700 | 1.0128 | 0.025 |
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- | 1.0276 | 0.7426 | 5800 | 1.0117 | 0.02 |
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- | 1.0212 | 0.7554 | 5900 | 1.0146 | 0.01 |
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- | 1.0253 | 0.7682 | 6000 | 1.0123 | 0.005 |
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- | 1.0032 | 0.7810 | 6100 | 1.0047 | 0.015 |
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- | 1.025 | 0.7939 | 6200 | 1.0070 | 0.02 |
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- | 1.0113 | 0.8067 | 6300 | 1.0010 | 0.035 |
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- | 1.0118 | 0.8195 | 6400 | 0.9992 | 0.03 |
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- | 1.0029 | 0.8323 | 6500 | 1.0026 | 0.005 |
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- | 1.0055 | 0.8451 | 6600 | 1.0011 | 0.0 |
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- | 1.0269 | 0.8579 | 6700 | 0.9993 | 0.01 |
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- | 1.0216 | 0.8707 | 6800 | 0.9979 | 0.015 |
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- | 1.018 | 0.8835 | 6900 | 0.9991 | 0.0 |
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- | 1.0099 | 0.8963 | 7000 | 0.9974 | 0.02 |
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- | 1.0254 | 0.9091 | 7100 | 0.9960 | 0.01 |
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- | 0.998 | 0.9219 | 7200 | 0.9938 | 0.025 |
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- | 1.0072 | 0.9347 | 7300 | 0.9929 | 0.015 |
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- | 1.0181 | 0.9475 | 7400 | 0.9921 | 0.01 |
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- | 1.0103 | 0.9603 | 7500 | 0.9929 | 0.005 |
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- | 0.9939 | 0.9731 | 7600 | 0.9923 | 0.01 |
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- | 1.0 | 0.9859 | 7700 | 0.9922 | 0.01 |
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- | 1.0301 | 0.9987 | 7800 | 0.9923 | 0.01 |
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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: 0.0000
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+ - Accuracy: 1.0
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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 | 2.6916 | 0.0 |
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+ | 1.9541 | 0.0320 | 100 | 1.9214 | 0.005 |
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+ | 0.9728 | 0.0641 | 200 | 1.0690 | 0.0 |
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+ | 0.9099 | 0.0961 | 300 | 0.7838 | 0.035 |
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+ | 0.481 | 0.1281 | 400 | 0.5249 | 0.18 |
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+ | 0.4591 | 0.1602 | 500 | 0.5097 | 0.235 |
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+ | 0.4191 | 0.1922 | 600 | 0.5116 | 0.285 |
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+ | 0.1323 | 0.2242 | 700 | 0.1011 | 0.775 |
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+ | 0.0385 | 0.2562 | 800 | 0.0188 | 0.985 |
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+ | 0.1343 | 0.2883 | 900 | 0.0617 | 0.86 |
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+ | 0.0199 | 0.3203 | 1000 | 0.0369 | 0.91 |
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+ | 0.0021 | 0.3523 | 1100 | 0.0085 | 0.98 |
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+ | 0.0779 | 0.3844 | 1200 | 0.0270 | 0.945 |
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+ | 0.0077 | 0.4164 | 1300 | 0.0044 | 0.995 |
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+ | 0.0165 | 0.4484 | 1400 | 0.0063 | 0.99 |
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+ | 0.0494 | 0.4805 | 1500 | 0.0651 | 0.87 |
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+ | 0.0012 | 0.5125 | 1600 | 0.0285 | 0.975 |
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+ | 0.0175 | 0.5445 | 1700 | 0.0108 | 0.99 |
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+ | 0.0001 | 0.5766 | 1800 | 0.0001 | 1.0 |
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+ | 0.0001 | 0.6086 | 1900 | 0.0001 | 1.0 |
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+ | 0.0 | 0.6406 | 2000 | 0.0000 | 1.0 |
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+ | 0.0001 | 0.6726 | 2100 | 0.0001 | 1.0 |
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+ | 0.0 | 0.7047 | 2200 | 0.0000 | 1.0 |
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+ | 0.0 | 0.7367 | 2300 | 0.0000 | 1.0 |
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+ | 0.0 | 0.7687 | 2400 | 0.0000 | 1.0 |
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+ | 0.0 | 0.8008 | 2500 | 0.0000 | 1.0 |
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+ | 0.0 | 0.8328 | 2600 | 0.0000 | 1.0 |
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+ | 0.0 | 0.8648 | 2700 | 0.0000 | 1.0 |
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+ | 0.0 | 0.8969 | 2800 | 0.0000 | 1.0 |
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+ | 0.0 | 0.9289 | 2900 | 0.0000 | 1.0 |
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+ | 0.0 | 0.9609 | 3000 | 0.0000 | 1.0 |
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+ | 0.0 | 0.9930 | 3100 | 0.0000 | 1.0 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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