safetensors en base_model:mistralai/Mistral-7B-v0.1 region:us
---
language:
- en
base_model: mistralai/Mistral-7B-v0.1
---
# Summary
The name is self-explanatory. This LoRA was trained on 50MB of text taken from Archive Of Our Own (AO3). In total, 1441 stories were selected from the Furry fandom category. I don't remember what filters I used. This LoRA is meant to improve a model's roleplaying capabilities, but I'll let you be the judge of that. Feel free to leave feedback, I'd like to hear your opinions on this LoRA.

# Dataset Settings
 - Context length: 4096
 - Epochs: 3

# LoRA Settings
 - Rank: 128
 - Alpha: 256
 - Targeted modules: Q, K, V, O, Gate, Up, Down
 - NEFTune alpha: 10 (to try to reduce overfitting)
 - Learning rate: 1e-4
 - Dropout: 0 (unsloth doesn't support LoRA dropout)

# Model Settings
 - Base model: Mistral 7B
 - Data Type: BF16, 4 bit quantization (thanks BitsandBytes)

# Misc Settings
 - Batch size: 2
 - Gradient Accumulation steps: 16
 - LR Scheduler: Linear

# Software and Hardware
 - Unsloth was used to speed up training. 
 - Training was done on 1x RTX 3090 (with 24 GB of VRAM) and took 11 hours.

# Warnings
 - Obviously, having been trained on AO3 fanfics, this LoRA will probably increase the chances of a model generating 18+ content. Furthermore, it is possible that, if prompted to do so, the LoRA may help generate illegal content. So yknow, don't ask it to do that.
 - Additionally, there is a chance this LoRA will output training data. The training graph seems to suggest that the LoRA was overfitting.

# Training Graph

![image/png](https://cdn-uploads.huggingface.co/production/uploads/64504e9be1d7a97f3b698682/0Zv-e-d3C4hwsWWZJbyB9.png)