NeoCyber
/

m-e5-small-vlsp2018-restaurant

Text Classification

absa_transformer

aspect-based-sentiment-analysis

multilingual-e5

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NeoCyber/m-e5-small-vlsp2018-restaurant

Aspect-based sentiment model exported from vlsp-2018-restaurant-e5-small-best.pt.

Training Metadata

Base model: intfloat/multilingual-e5-small
Epoch: 17
Multi branch: False
Aspect count: 12
Sentiment labels: none, positive, negative, neutral

Training Dataset

Dataset: VLSP 2018 Sentiment Analysis - Restaurant
Local dataset path: training/datasets/vlsp2018_restaurant
Result source: training/pipeline/full_pipeline_res.ipynb

Test Metrics (Weighted Avg)

Report	Precision	Recall	F1	Support
aspect_category	0.816910	0.825833	0.815224	6000
aspect_category_polarity	0.749515	0.755833	0.733340	6000

Checkpoint Metrics

{
  "loss": 0.40864819120014867,
  "accuracy": 0.8805555555555555,
  "f1": 0.608023406518321
}

Aspects

AMBIENCE#GENERAL
DRINKS#PRICES
DRINKS#QUALITY
DRINKS#STYLE&OPTIONS
FOOD#PRICES
FOOD#QUALITY
FOOD#STYLE&OPTIONS
LOCATION#GENERAL
RESTAURANT#GENERAL
RESTAURANT#MISCELLANEOUS
RESTAURANT#PRICES
SERVICE#GENERAL

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Safetensors

Model size

0.1B params

Tensor type

F32

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Model tree for NeoCyber/m-e5-small-vlsp2018-restaurant

Base model

intfloat/multilingual-e5-small

Finetuned

(178)

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