Модель OuteAI/Lite-Oute-1-300M-Instruct дообученная на датасете cardiffnlp/tweet_eval, задача классификации сентимента твита, вывести одно из трех слов - negative, neutral, positive.

Дообучение

Модель дообучалась при помощи LoRA.

Ранг LoRA = 8
alpha=16
LoRA применялась только к весам Key, Value в attention
BATCH_SIZE = 16
LEARNING_RATE = 2e-4
NUM_EPOCHS = 2
AdamW

Метрика на валидации

F1=0.53

Примеры генерации

Tweet: "QT @user In the original draft of the 7th book, Remus Lupin survived the Battle of Hogwarts. #HappyBirthdayRemusLupin"
Label: positive
Output:
positive
positive
positive

Tweet: "Ben Smith / Smith (concussion) remains out of the lineup Thursday, Curtis #NHL #SJ"
Label: neutral
Output:
neutral
neutral
neutral
neut

Tweet: Sorry bout the stream last night I crashed out but will be on tonight for sure. Then back to Minecraft in pc tomorrow night.
Label: neutral
Output:
neutral
positive
positive
pos

Tweet: Chase Headley's RBI double in the 8th inning off David Price snapped a Yankees streak of 33 consecutive scoreless innings against Blue Jays
Label: neutral
Output:
neutral
neutral
neutral
neut

Tweet: @user Alciato: Bee will invest 150 million in January, another 200 in the Summer and plans to bring Messi by 2017"
Label: positive
Output:
neutral
neutral
neutral
neut

Downloads last month: 1

Model tree for mcnckc/llm-course-hw3-lora

Base model

OuteAI/Lite-Oute-1-300M-Instruct

Finetuned

(29)

this model

Dataset used to train mcnckc/llm-course-hw3-lora

Collection including mcnckc/llm-course-hw3-lora

LLM-HW3

Collection

Коллекция моделей, дообученных с помощью низкоранговых адаптаций на задачу классификации сентимента твита • 3 items • Updated Mar 29, 2025