---
license: apache-2.0
datasets:
- legacy-datasets/banking77
language:
- en
metrics:
- accuracy
base_model:
- bert-base-uncased
pipeline:
- GEM_pipeline
---

# GEM_Banking77 Model Card

This model card provides an overview of the GEM_Banking77 model, a fine-tuned implementation of the GEM architecture designed for the **Banking77** dataset.

## Purpose

The GEM_Banking77 model was developed to evaluate the performance of the **GEM architecture** on **domain-specific datasets**, particularly in the banking and financial sector. The **Banking77 dataset**, a benchmark for **intent classification**, was chosen to assess the model’s effectiveness.

## Key Details

- **License**: Apache-2.0  
- **Dataset**: `legacy-datasets/banking77`  
- **Language**: English  
- **Metrics**: Accuracy: **92.56%**  
- **Base Model**: bert-base-uncased  
- **Pipeline**: GEM_pipeline  

## Model Details

The GEM_Banking77 model is built on the **GEM architecture** and fine-tuned from `bert-base-uncased` using the **Banking77 dataset**. The model configuration is as follows:

- **Number of epochs**: **10**  
- **Batch size**: **Dynamic scaling: 32 * number of GPUs**  
- **Learning rate**: **2e-5**  
- **Maximum sequence length**: **128**  
- **Gradient accumulation steps**: **2**  
- **Cluster size**: **256**  
- **Number of domains**: **8**  
- **Number of classes**: **77**  
- **Number of attention heads**: **12**  

## Training & Evaluation

The model was trained using the **GEM_pipeline** and evaluated using **accuracy**, achieving a score of **92.56%**.