Qwen2.5-3B — LoRA adapter for Marketplace Review Category Classification
Model Details
This repository contains a LoRA adapter trained to classify marketplace customer reviews into product categories. The adapter was fine-tuned on a downstream sequence-classification task and is intended to be used with the Qwen/Qwen2.5-3B base model using the PEFT library.
Model Description
Adapter type: LoRA (PEFT)
Base model:
Qwen/Qwen2.5-3BTask: Multiclass text classification (product category of marketplace reviews)
Labels (classes):
- бытовая техника (home appliances)
- обувь (shoes)
- одежда (clothing)
- посуда (tableware / kitchenware)
- текстиль (textiles)
- товары для детей (kids / baby products)
- украшения и аксессуары (jewelry & accessories)
- электроника (electronics)
- нет товара (NO_PRODUCT)
Developed by: [More Information Needed]
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Model type: [More Information Needed]
Language(s) (NLP): [More Information Needed]
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Finetuned from model [optional]: [More Information Needed]
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How to load (inference)
Install prerequisites:
pip install transformers peft safetensors huggingface_hub
# If you want 8-bit:
pip install bitsandbytes
Training Details
Training Data
LORA_R = 64
LORA_ALPHA = 128
LORA_DROPOUT = 0.10
NUM_EPOCHS = 5
PER_DEVICE_BATCH_SIZE = 1
GRAD_ACCUM_STEPS = 8
LEARNING_RATE = 2e-4
WEIGHT_DECAY = 0.01
WARMUP_RATIO = 0.03
MAX_SEQ_LENGTH = 256
SEED = 42
Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
- Hardware Type: [More Information Needed]
- Hours used: [More Information Needed]
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- Carbon Emitted: [More Information Needed]
Framework versions
- PEFT 0.15.2
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Model tree for DikovAlexandr/Qwen2.5-3B-LoAR-Classifier
Base model
Qwen/Qwen2.5-3B