See axolotl config axolotl version: 0.4.1 mistral fine out This model is a fine tuned version of mistralai/Mistral 7B Instruct v0.3 on a synthetic appeals dataset. See the health insurance fine tuning repo for details. An earlier version of this dataset is availabile. It achieves the following results on the evaluation set: Loss: 0.7984 Model description Generate health insurance appeals. Early work. Intended uses & limitations It is intended to be used as part of the fight health insurance web app who's repo is at https://github.com/totallylegitco/fighthealthinsurance Training and evaluation data More information needed Training procedure Training hyperparameters The following hyperparameters were used during training: learning rate: 5e 06 train batch size: 2 eval batch size: 2 seed: 42 gradient accumulation steps: 4 total train batch size: 8 optimizer: Adam with betas=(0.9,0.999) and epsilon=1e 08 lr scheduler type: cosine lr scheduler warmup steps: 10 num epochs: 2 Training results Training Loss Epoch Step Validation Loss : : : : : : : : 1.0397 0.0004 1 1.1590 0.6084 0.1002 230 0.7272 0.5195 0.2003 460 0.7141 0.4713 0.3005 690 0.7090 0.3973 0.4007 920 0.7097 0.3306 0.5009 1150 0…
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