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Absa 10 Domains Lora Base by SilvioLima

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  Adapter   Code   Dataset:silviolima/absa   Dataset:silviolima/raw data Dataset:silviolima/raw data au...   En   Finetuned   License:apache-2.0   Lora   Peft   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/SilvioLima/absa_10_domains_lora_base 
Absa 10 Domains Lora Base (SilvioLima/absa_10_domains_lora_base)

Absa 10 Domains Lora Base Parameters and Internals

Model Type 
text generation
Use Cases 
Areas:
e-commerce, review sentiment analysis
Applications:
Identifying aspects, opinions, and polarities in text reviews
Primary Use Cases:
Aspect-based sentiment analysis of product reviews
Additional Notes 
The model uses a paraphrasing technique to extract sentiment-related features from reviews. It requires sufficient computational resources to handle data inputs efficiently.
Training Details 
Data Sources:
10k reviews from an e-commerce site across 10 domains
Data Volume:
13513 reviews in total
Methodology:
Trained using a paraphrasing approach. The model was given example sentences and instructed to rewrite them in the same format, emphasizing identified aspects, opinions, and polarities.
Hardware Used:
VM in GCP with configurations to handle the memory constraints
Model Architecture:
Based on the google/flan-t5-base model with LORA configuration for training
Input Output 
Input Format:
Follow example format given during training.
Accepted Modalities:
text
Output Format:
Paraphrased text highlighting aspects, opinions, and polarities.
LLM NameAbsa 10 Domains Lora Base
Repository 🤗https://huggingface.co/SilvioLima/absa_10_domains_lora_base 
Required VRAM0 GB
Updated2024-07-04
MaintainerSilvioLima
Model Files  0.0 GB   0.0 GB
Supported Languagesen
Model ArchitectureAdapter
Licenseapache-2.0
Model Max Length512
Is Biasednone
Tokenizer ClassT5Tokenizer
Padding Token<pad>
PEFT TypeLORA
LoRA ModelYes
PEFT Target Modulesv|q
LoRA Alpha32
LoRA Dropout0.1
R Param16

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Note: green Score (e.g. "73.2") means that the model is better than SilvioLima/absa_10_domains_lora_base.

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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Release v20241227
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