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README.md
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[Axolotl](https://github.com/OpenAccess-AI-Collective/axolotl) was used for training
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on one NVidia RTX3090.
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The training data consisted of **43** conversations (171k tokens /
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of roughly 4k tokens length. The learning rate is the one that about minimizes the
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eval loss on one epoch with a constant learning schedule. For the following two epochs
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what would be normally considered overfitting occurs, but at the same time output
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[Axolotl](https://github.com/OpenAccess-AI-Collective/axolotl) was used for training
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on one NVidia RTX3090.
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152 |
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+
The training data consisted of **43** conversations (171k tokens / 963 messages)
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of roughly 4k tokens length. The learning rate is the one that about minimizes the
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155 |
eval loss on one epoch with a constant learning schedule. For the following two epochs
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156 |
what would be normally considered overfitting occurs, but at the same time output
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