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Fine-tuned GPT-2 on Wikitext-2

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README.md CHANGED
@@ -15,7 +15,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [cuba6112/orion](https://huggingface.co/cuba6112/orion) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 3.7863
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  ## Model description
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@@ -48,40 +48,40 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:------:|:-----:|:---------------:|
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- | No log | 0.0871 | 400 | 4.0717 |
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- | 1.1036 | 0.1743 | 800 | 4.2755 |
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- | 0.5557 | 0.2614 | 1200 | 4.2846 |
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- | 0.5875 | 0.3486 | 1600 | 4.3302 |
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- | 0.7643 | 0.4357 | 2000 | 4.2009 |
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- | 0.7643 | 0.5229 | 2400 | 4.2351 |
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- | 0.8454 | 0.6100 | 2800 | 4.1802 |
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- | 0.8842 | 0.6972 | 3200 | 4.1432 |
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- | 0.9623 | 0.7843 | 3600 | 4.1293 |
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- | 1.035 | 0.8715 | 4000 | 4.1069 |
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- | 1.035 | 0.9586 | 4400 | 4.0661 |
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- | 1.0997 | 1.0458 | 4800 | 4.1568 |
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- | 0.9309 | 1.1329 | 5200 | 4.1577 |
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- | 0.9472 | 1.2200 | 5600 | 4.1401 |
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- | 0.9693 | 1.3072 | 6000 | 4.0909 |
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- | 0.9693 | 1.3943 | 6400 | 4.1024 |
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- | 0.9997 | 1.4815 | 6800 | 4.0739 |
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- | 1.0231 | 1.5686 | 7200 | 4.0358 |
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- | 1.0753 | 1.6558 | 7600 | 4.0478 |
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- | 1.0979 | 1.7429 | 8000 | 4.0195 |
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- | 1.0979 | 1.8301 | 8400 | 3.9682 |
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- | 1.1759 | 1.9172 | 8800 | 3.9687 |
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- | 1.1717 | 2.0044 | 9200 | 3.9502 |
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- | 1.126 | 2.0915 | 9600 | 3.9832 |
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- | 1.1136 | 2.1786 | 10000 | 3.9696 |
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- | 1.1136 | 2.2658 | 10400 | 3.9509 |
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- | 1.1521 | 2.3529 | 10800 | 3.9246 |
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- | 1.186 | 2.4401 | 11200 | 3.9041 |
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- | 1.2276 | 2.5272 | 11600 | 3.8872 |
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- | 1.2686 | 2.6144 | 12000 | 3.8677 |
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- | 1.2686 | 2.7015 | 12400 | 3.8415 |
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- | 1.3043 | 2.7887 | 12800 | 3.8204 |
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- | 1.3474 | 2.8758 | 13200 | 3.8007 |
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- | 1.3954 | 2.9630 | 13600 | 3.7884 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [cuba6112/orion](https://huggingface.co/cuba6112/orion) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 3.8830
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:------:|:-----:|:---------------:|
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+ | No log | 0.0871 | 400 | 4.2671 |
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+ | 1.0011 | 0.1743 | 800 | 4.5104 |
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+ | 0.4041 | 0.2614 | 1200 | 4.5219 |
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+ | 0.4304 | 0.3486 | 1600 | 4.5754 |
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+ | 0.5773 | 0.4357 | 2000 | 4.4567 |
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+ | 0.5773 | 0.5229 | 2400 | 4.4879 |
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+ | 0.6563 | 0.6100 | 2800 | 4.4276 |
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+ | 0.6965 | 0.6972 | 3200 | 4.4034 |
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+ | 0.7728 | 0.7843 | 3600 | 4.3906 |
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+ | 0.8479 | 0.8715 | 4000 | 4.3692 |
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+ | 0.8479 | 0.9586 | 4400 | 4.3255 |
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+ | 0.9187 | 1.0458 | 4800 | 4.4073 |
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+ | 0.7619 | 1.1329 | 5200 | 4.4022 |
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+ | 0.7889 | 1.2200 | 5600 | 4.3840 |
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+ | 0.8156 | 1.3072 | 6000 | 4.3322 |
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+ | 0.8156 | 1.3943 | 6400 | 4.3391 |
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+ | 0.8547 | 1.4815 | 6800 | 4.2961 |
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+ | 0.8862 | 1.5686 | 7200 | 4.2534 |
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+ | 0.9424 | 1.6558 | 7600 | 4.2652 |
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+ | 0.9764 | 1.7429 | 8000 | 4.2246 |
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+ | 0.9764 | 1.8301 | 8400 | 4.1637 |
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+ | 1.0649 | 1.9172 | 8800 | 4.1581 |
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+ | 1.0692 | 2.0044 | 9200 | 4.1303 |
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+ | 1.0272 | 2.0915 | 9600 | 4.1594 |
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+ | 1.0207 | 2.1786 | 10000 | 4.1426 |
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+ | 1.0207 | 2.2658 | 10400 | 4.1154 |
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+ | 1.0669 | 2.3529 | 10800 | 4.0789 |
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+ | 1.1129 | 2.4401 | 11200 | 4.0485 |
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+ | 1.1645 | 2.5272 | 11600 | 4.0232 |
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+ | 1.2151 | 2.6144 | 12000 | 3.9955 |
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+ | 1.2151 | 2.7015 | 12400 | 3.9612 |
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+ | 1.262 | 2.7887 | 12800 | 3.9308 |
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+ | 1.3164 | 2.8758 | 13200 | 3.9033 |
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+ | 1.3759 | 2.9630 | 13600 | 3.8860 |
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  ### Framework versions
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