gtfintechlab
/

model_central_bank_of_chile_time_label

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 ---
-library_name: transformers
-tags: []
----
-# Model Card for Model ID
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 ---
+license: cc-by-nc-sa-4.0
+datasets:
+- gtfintechlab/central_bank_of_chile
+language:
+- en
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+base_model:
+- roberta-base
+pipeline_tag: text-classification
+library_name: transformers
+---
+# World of Central Banks Model
+**Model Name:** Central Bank of Chile Temporal Classification Model
+**Model Type:** Text Classification
+**Language:** English
+**License:** [CC-BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/deed.en)
+**Base Model:** [roberta-base](https://huggingface.co/FacebookAI/roberta-base)
+**Dataset Used for Training:** [gtfintechlab/central_bank_of_chile](https://huggingface.co/datasets/gtfintechlab/central_bank_of_chile)
+## Model Overview
+Central Bank of Chile Temporal Classification Model is a fine-tuned roberta-base model designed to classify text data on **Temporal Classification**. This label is annotated in the central_bank_of_chile dataset, which focuses on meeting minutes for the Central Bank of Chile.
+## Intended Use
+This model is intended for researchers and practitioners working on subjective text classification for the Central Bank of Chile, particularly within financial and economic contexts. It is specifically designed to assess the **Temporal Classification** label, aiding in the analysis of subjective content in financial and economic communications.
+## How to Use
+To utilize this model, load it using the Hugging Face `transformers` library:
+```python
+from transformers import pipeline, AutoTokenizer, AutoModelForSequenceClassification, AutoConfig
+# Load tokenizer, model, and configuration
+tokenizer = AutoTokenizer.from_pretrained("gtfintechlab/central_bank_of_chile", do_lower_case=True, do_basic_tokenize=True)
+model = AutoModelForSequenceClassification.from_pretrained("gtfintechlab/central_bank_of_chile", num_labels=2)
+config = AutoConfig.from_pretrained("gtfintechlab/central_bank_of_chile")
+# Initialize text classification pipeline
+classifier = pipeline('text-classification', model=model, tokenizer=tokenizer, config=config, framework="pt")
+# Classify Temporal Classification
+sentences = [
+    "[Sentence 1]",
+    "[Sentence 2]"
+]
+results = classifier(sentences, batch_size=128, truncation="only_first")
+print(results)
+```
+In this script:
+- **Tokenizer and Model Loading:**
+  Loads the pre-trained tokenizer and model from `gtfintechlab/central_bank_of_chile`.
+- **Configuration:**
+  Loads model configuration parameters, including the number of labels.
+- **Pipeline Initialization:**
+  Initializes a text classification pipeline with the model, tokenizer, and configuration.
+- **Classification:**
+  Labels sentences based on **Temporal Classification**.
+Ensure your environment has the necessary dependencies installed.
+## Label Interpretation
+- **LABEL_0:** Forward-looking; the sentence discusses future economic events or decisions.
+- **LABEL_1:** Not forward-looking; the sentence discusses past or current economic events or decisions.
+## Training Data
+The model was trained on the central_bank_of_chile dataset, comprising annotated sentences from the Central Bank of Chile meeting minutes, labeled by **Temporal Classification**. The dataset includes training, validation, and test splits.
+## Citation
+If you use this model in your research, please cite the central_bank_of_chile:
+```bibtex
+@article{WCBShahSukhaniPardawala,
+  title={Words That Unite The World: A Unified Framework for Deciphering Global Central Bank Communications},
+  author={Agam Shah, Siddhant Sukhani, Huzaifa Pardawala et al.},
+  year={2025}
+}
+```
+For more details, refer to the [central_bank_of_chile dataset documentation](https://huggingface.co/gtfintechlab/central_bank_of_chile).
+## Contact
+For any central_bank_of_chile related issues and questions, please contact:
+- Huzaifa Pardawala: huzaifahp7[at]gatech[dot]edu
+- Siddhant Sukhani: ssukhani3[at]gatech[dot]edu
+- Agam Shah: ashah482[at]gatech[dot]edu