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--- |
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base_model: unsloth/Mistral-Nemo-Base-2407 |
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library_name: peft |
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license: apache-2.0 |
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tags: |
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- axolotl |
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- generated_from_trainer |
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model-index: |
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- name: adventure-nemo-ws |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) |
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# adventure-nemo-QLoRA |
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Another QLoRA on Mistral Nemo Base, this time with Spring Dragon *and* Skein data included. ~29M tokens total of text adventure data. |
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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. |
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This method of use is set up as default in Kobold Lite's Adventure mode. |
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**Again, no instruct format was trained into this.** |
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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. |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.00025 |
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- train_batch_size: 4 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine_with_min_lr |
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- lr_scheduler_warmup_steps: 10 |
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- num_epochs: 1 |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.45.0.dev0 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
