chaymaemerhrioui/ACC_Dataset
Viewer • Updated • 1k • 12 • 1
How to use chaymaemerhrioui/mistral-Brain_Model_ACC_Trainer with PEFT:
from peft import PeftModel
from transformers import AutoModelForCausalLM
base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.3")
model = PeftModel.from_pretrained(base_model, "chaymaemerhrioui/mistral-Brain_Model_ACC_Trainer")This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.3 on an unknown dataset. It achieves the following results on the evaluation set:
The system in question incorporates a sophisticated model designed to process user-provided inputs, specifically descriptions of various systems, and subsequently generate comprehensive and detailed descriptions of those systems. By analyzing the initial input, the model effectively elaborates on the provided information, producing an extensive and formalized depiction that enhances the understanding and documentation of the system described.
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.0754 | 0.1 | 20 | 0.9337 |
| 0.5144 | 0.2 | 40 | 0.3974 |
| 0.2526 | 0.3 | 60 | 0.2197 |
| 0.193 | 0.4 | 80 | 0.1900 |
| 0.1939 | 0.5 | 100 | 0.1733 |
| 0.1695 | 0.6 | 120 | 0.1645 |
| 0.1739 | 0.7 | 140 | 0.1567 |
| 0.1511 | 0.8 | 160 | 0.1504 |
| 0.1484 | 0.9 | 180 | 0.1462 |
| 0.1419 | 1.0 | 200 | 0.1435 |
| 0.1467 | 1.1 | 220 | 0.1410 |
| 0.1315 | 1.2 | 240 | 0.1384 |
| 0.1344 | 1.3 | 260 | 0.1370 |
| 0.1411 | 1.4 | 280 | 0.1355 |
| 0.1338 | 1.5 | 300 | 0.1346 |
| 0.128 | 1.6 | 320 | 0.1324 |
| 0.1312 | 1.7 | 340 | 0.1328 |
| 0.1191 | 1.8 | 360 | 0.1312 |
| 0.1228 | 1.9 | 380 | 0.1301 |
| 0.1317 | 2.0 | 400 | 0.1291 |
| 0.1152 | 2.1 | 420 | 0.1291 |
| 0.1167 | 2.2 | 440 | 0.1285 |
| 0.1178 | 2.3 | 460 | 0.1283 |
| 0.1184 | 2.4 | 480 | 0.1268 |
| 0.118 | 2.5 | 500 | 0.1267 |
| 0.1104 | 2.6 | 520 | 0.1258 |
| 0.1128 | 2.7 | 540 | 0.1254 |
| 0.1113 | 2.8 | 560 | 0.1249 |
| 0.1174 | 2.9 | 580 | 0.1247 |
| 0.1081 | 3.0 | 600 | 0.1245 |
Base model
mistralai/Mistral-7B-v0.3