---
base_model: unsloth/gemma-3n-e4b-it-unsloth-bnb-4bit
tags:
- text-generation-inference
- transformers
- unsloth
- gemma3n
license: apache-2.0
language:
- en
datasets:
- chimbiwide/pippa_filtered
---

# Gemma3NPC-filtered-float16

#### The "filtered" model that delivers censored general role-playing at great speed.

We trained this model as a rank-12 LoRA adapter with one epoch over `pippa_filtered` using a 40GB vRAM A100 in Google Colab. For this run, we employed a learning rate of `2e-5` and a total batch size of 1 and gradient accumulation steps of 16. A cosine learning rate scheduler was used with a 150-step warmup. With a gradient clipping of 0.5.

Check out our training notebook [here](https://github.com/chimbiwide/Gemma3NPC/blob/main/Training/Gemma3NPC-Filtered.ipynb).

---

Here is a graph of the Step Training Loss, saved every 5 steps:

![image/png](https://cdn-uploads.huggingface.co/production/uploads/67d5b5a056a9d31aa0b49687/lr8ubWOj6HCo_cH_L023o.png)