Mistral-Nemo-12B-Adventure-QLoRA

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Mistral-Nemo-12B-Adventure-QLoRA

Another QLoRA on Mistral Nemo Base, this time with Spring Dragon and Skein data included. ~29M tokens total of text adventure data.

This was trained in completion format where user input is given as > User input. Set > as a stopping string and preface your input with > to use with classic text completion mode.

This method of use is set up as default in Kobold Lite's Adventure mode.

Again, no instruct format was trained into this.

Apply to a Nemo model and use whatever instruct format that model uses - the style (and deadliness) of the LoRA carries over to instruct usage as well.

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 0.00025
• train_batch_size: 4
• eval_batch_size: 1
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine_with_min_lr
• lr_scheduler_warmup_steps: 10
• num_epochs: 1

Framework versions

• PEFT 0.12.0
• Transformers 4.45.0.dev0
• Pytorch 2.3.1+cu121
• Datasets 2.21.0
• Tokenizers 0.19.1