medquad-lora-r32

CHF0101/medquad-lora-r32

medquad-lora-r32 is a machine learning model from CHF0101. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as apache-2.0.

- Base: mistralai/Mistral-7B-Instruct-v0.3 - LoRA r: 32 - Módulos: qproj, kproj, vproj - 4-bit NF4 - Early Stopping: patience=3 Training logs (manual, Epoch estimado):

Downloads · 30 days

35% of all-time downloads

All-time downloads

Public

Repo size

75.5 MB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors75.5 MB · 100%

At a glance

Library: peft
License: apache-2.0
Access: Public
Created: Oct 29, 2025
Updated: Nov 2, 2025
SHA: 56f2710e

Model card

From the Hugging Face model README

MedQuAD LoRA r=32

Configuración

Base: mistralai/Mistral-7B-Instruct-v0.3
LoRA r: 32
Módulos: q_proj, k_proj, v_proj
4-bit NF4
Early Stopping: patience=3

Entrenamiento

Training logs (manual, Epoch estimado):

Step	Epoch	Training Loss	Validation Loss
100	0.046	0.824200	0.792224
200	0.093	0.766400	0.763532
300	0.139	0.761900	0.749713
400	0.186	0.734200	0.737889
500	0.232	0.728500	0.727421
600	0.279	0.734900	0.719858
700	0.325	0.715400	0.706352
800	0.371	0.722500	0.695117
900	0.418	0.702000	0.687702
1000	0.464	0.686500	0.677177
1100	0.511	0.674400	0.673650
1200	0.557	0.646700	0.663053
1300	0.604	0.651100	0.662174

Uso

from peft import PeftModel
from transformers import AutoModelForCausalLM
base = AutoModelForCausalLM.from_pretrained('mistralai/Mistral-7B-Instruct-v0.3', load_in_4bit=True)
model = PeftModel.from_pretrained(base, 'CHF0101/medquad-lora-r32')

Library: peft
License: apache-2.0
Languages: en
Created: Oct 29, 2025
Updated: Nov 2, 2025