---
base_model: unsloth/Mistral-Nemo-Base-2407
library_name: peft
license: apache-2.0
tags:
- axolotl
- generated_from_trainer
model-index:
- name: adventure-nemo-ws
  results: []
---

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# adventure-nemo-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