ESG-classification
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ESG analysis can help investors determine a business' long-term sustainability and identify associated risks. ViDistilBERT-ESG-base is a distilbert/distilbert-base-multilingual-cased model fine-tuned on ViEn-ESG-100 dataset, include 100,000 annotated sentences from Vietnam, English news and ESG reports.
Input: A financial text.
Output: Environmental, Social, Governance or None.
Language support: English, Vietnamese
You can use this model with Transformers pipeline for ESG classification.
# tested in transformers==4.51.0 
from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
esgbert = AutoModelForSequenceClassification.from_pretrained('nguyen599/ViDistilBERT-ESG-base',num_labels=4)
tokenizer = AutoTokenizer.from_pretrained('nguyen599/ViDistilBERT-ESG-base')
nlp = pipeline("text-classification", model=esgbert, tokenizer=tokenizer)
results = nlp('Over three chapters, it covers a range of topics from energy efficiency and renewable energy to the circular economy and sustainable transportation.')
print(results) # [{'label': 'Environment', 'score': 0.9206041026115417}]
F1 scores of models on each ESG category in the English ViEn-ESG-100 dataset.
| Model | Backbone | Param | E | S | G | N | 
|---|---|---|---|---|---|---|
| SEC-BERT-ft | SEC-BERT-base | 109M | 83.12 | 66.77 | 66.53 | 60.30 | 
| FinBERT-ESG | FinBERT | 109M | 92.67 | 84.90 | 86.25 | 87.26 | 
| FinBERT-ESG-9-class | FinBERT | 109M | 92.16 | 89.01 | 91.35 | 86.89 | 
| ESGify | MPNet-base | 109M | 67.72 | 30.20 | 50.76 | 43.44 | 
| EnvironmentBERT | DistilRoBERTa | 82M | 92.15 | - | - | 92.76 | 
| SocialBERT | DistilRoBERTa | 82M | - | 76.81 | - | 81.23 | 
| GovernanceBERT | DistilRoBERTa | 82M | - | - | 64.46 | 80.06 | 
| ViBERT-ESG(Our) | BERT-base-cased | 168M | 93.76 | 94.53 | 94.98 | 94.15 | 
| ViRoBERTa-ESG(Our) | RoBERTa-base | 124M | 95.43 | 94.06 | 95.01 | 91.32 | 
| ViXLMRoBERTa-ESG(Our) | XLM-RoBERTa-base | 278M | 95.00 | 95.00 | 95.47 | 92.19 | 
| ViDeBERTa-ESG(Our) | DeBERTa-v3-base | 184M | 95.50 | 94.49 | 94.81 | 91.48 | 
| ViDeBERTa-small-ESG(Our) | DeBERTa-v3-small | 141M | 94.55 | 94.85 | 94.58 | 90.19 | 
| ViDistilBERT-ESG(Our) | DistilBERT-base-cased | 135M | 95.15 | 95.19 | 94.33 | 91.75 | 
| ViBERT-Env(Our) | BERT-base-cased | 168M | 94.62 | - | - | 92.13 | 
| ViBERT-Soc(Our) | BERT-base-cased | 168M | - | 94.86 | - | 92.22 | 
| ViBERT-Gov(Our) | BERT-base-cased | 168M | - | - | 93.47 | 93.82 | 
F1 scores of models on each ESG category in the Vietnamese ViEn-ESG-100 dataset.
| Model | Backbone | Param | E | S | G | N | 
|---|---|---|---|---|---|---|
| ViBERT-ESG | BERT-base-cased | 168M | 93.50 | 89.73 | 91.77 | 91.78 | 
| ViRoBERTa-ESG | RoBERTa-base | 124M | 93.41 | 91.49 | 89.93 | 84.32 | 
| ViXLMRoBERTa-ESG | XLM-RoBERTa-base | 278M | 93.45 | 91.02 | 91.69 | 90.41 | 
| ViDeBERTa-ESG | DeBERTa-v3-base | 184M | 95.24 | 89.36 | 93.18 | 85.23 | 
| ViDeBERTa-small-ESG | DeBERTa-v3-small | 141M | 92.90 | 87.79 | 90.63 | 81.48 | 
| ViDistilBERT-ESG | DistilBERT-base-cased | 135M | 93.87 | 91.98 | 90.63 | 87.17 | 
| ViBERT-Env | BERT-base-cased | 168M | 94.87 | - | - | 91.15 | 
| ViBERT-Soc | BERT-base-cased | 168M | - | 91.07 | - | 90.29 | 
| ViBERT-Gov | BERT-base-cased | 168M | - | - | 92.62 | 90.11 |