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End of training
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README.md
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@@ -12,9 +12,9 @@ should probably proofread and complete it, then remove this comment. -->
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# my_rugpt3medium_finetune
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This model is a fine-tuned version of [ai-forever/rugpt3medium_based_on_gpt2](https://huggingface.co/ai-forever/rugpt3medium_based_on_gpt2) on
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It achieves the following results on the evaluation set:
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- Loss:
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## Model description
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@@ -49,60 +49,21 @@ The following hyperparameters were used during training:
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| Training Loss | Epoch | Step | Validation Loss |
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| 8.522 | 7.36 | 400 | 8.2732 |
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| 8.4227 | 7.82 | 425 | 8.1704 |
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| 8.3083 | 8.28 | 450 | 8.0290 |
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| 8.1897 | 8.74 | 475 | 7.8989 |
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| 8.0876 | 9.2 | 500 | 7.7778 |
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| 7.9824 | 9.66 | 525 | 7.6368 |
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| 7.8762 | 10.12 | 550 | 7.4974 |
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| 7.7408 | 10.58 | 575 | 7.3658 |
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| 7.6855 | 11.04 | 600 | 7.2416 |
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| 7.5163 | 11.5 | 625 | 7.1291 |
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| 7.5079 | 11.96 | 650 | 7.0295 |
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| 7.2873 | 12.42 | 675 | 6.8522 |
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| 7.2856 | 12.88 | 700 | 6.7573 |
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| 7.0868 | 13.34 | 725 | 6.6651 |
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| 7.0886 | 13.8 | 750 | 6.5239 |
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| 6.9283 | 14.26 | 775 | 6.3561 |
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| 6.8257 | 14.72 | 800 | 6.2392 |
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| 6.7328 | 15.18 | 825 | 6.1004 |
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| 6.6153 | 15.64 | 850 | 5.9846 |
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| 6.5824 | 16.1 | 875 | 5.8627 |
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| 6.3905 | 16.56 | 900 | 5.7724 |
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| 6.359 | 17.02 | 925 | 5.6321 |
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| 6.1679 | 17.48 | 950 | 5.5329 |
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| 6.1526 | 17.94 | 975 | 5.4058 |
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| 5.9604 | 18.4 | 1000 | 5.3046 |
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| 5.9669 | 18.87 | 1025 | 5.1939 |
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| 5.6807 | 19.33 | 1050 | 5.0499 |
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| 5.7445 | 19.79 | 1075 | 4.9479 |
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| 5.6578 | 20.25 | 1100 | 4.8343 |
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| 5.4919 | 20.71 | 1125 | 4.7547 |
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| 5.4427 | 21.17 | 1150 | 4.6506 |
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| 5.3212 | 21.63 | 1175 | 4.5628 |
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| 5.2953 | 22.09 | 1200 | 4.4814 |
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| 5.1872 | 22.55 | 1225 | 4.4373 |
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| 5.1285 | 23.01 | 1250 | 4.3966 |
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| 5.047 | 23.47 | 1275 | 4.3611 |
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| 5.0698 | 23.93 | 1300 | 4.3520 |
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| 5.1259 | 24.39 | 1325 | 4.3408 |
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| 4.9851 | 24.85 | 1350 | 4.3387 |
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### Framework versions
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# my_rugpt3medium_finetune
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This model is a fine-tuned version of [ai-forever/rugpt3medium_based_on_gpt2](https://huggingface.co/ai-forever/rugpt3medium_based_on_gpt2) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 7.6538
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## Model description
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 10.9229 | 1.6 | 25 | 10.5844 |
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| 10.3434 | 3.19 | 50 | 9.8909 |
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| 9.8567 | 4.79 | 75 | 9.5807 |
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| 9.6367 | 6.38 | 100 | 9.4535 |
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| 9.5384 | 7.98 | 125 | 9.3692 |
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| 9.4568 | 9.57 | 150 | 9.2894 |
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| 9.3755 | 11.17 | 175 | 9.1763 |
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| 9.2723 | 12.77 | 200 | 9.0257 |
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| 9.1276 | 14.36 | 225 | 8.8652 |
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| 9.0174 | 15.96 | 250 | 8.6803 |
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| 8.8551 | 17.55 | 275 | 8.5146 |
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| 8.7365 | 19.15 | 300 | 8.2912 |
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| 8.5503 | 20.74 | 325 | 8.0806 |
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| 8.4153 | 22.34 | 350 | 7.8582 |
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| 8.266 | 23.94 | 375 | 7.6538 |
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### Framework versions
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model.safetensors
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runs/Dec28_07-49-52_29de5df9d89b/events.out.tfevents.1703749797.29de5df9d89b.2425.0
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training_args.bin
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