---
_name_or_path: CustomGPT2ConversationalModel
torch_dtype: float32
transformers_version: 4.37.2
language: en
license: apache-2.0
metrics:
- perplexity
- accuracy
widget:
- text: >-
    Write a story about a character who discovers a mysterious artifact that
    grants them unexpected powers.
- text: Compose a poem about the beauty of nature and the passage of time.
- text: >-
    Generate a promotional announcement for a new technology that revolutionizes
    communication across cultures.
- text: >-
    Create a conversation between two individuals from different backgrounds
    discussing their dreams and aspirations.
- text: >-
    Draft an article exploring the role of technology in shaping future
    societies.
- text: >-
    Write a motivational speech encouraging people to pursue their passions and
    overcome obstacles.
- text: >-
    Imagine a world where magic is real and write a narrative about a quest to
    unlock its secrets.
- text: >-
    Compose a letter from a historical figure to a contemporary artist, sharing
    insights on creativity and innovation.
- text: >-
    Create a recipe for a delicious meal using only ingredients found in a
    futuristic sci-fi setting.
pipeline_tag: text-generation
---


🎉 Introducing **CustomGPT2Conversational** 🤖

🚀 Dive into the world of limitless conversations with our fine-tuned model!

🎨 **Unique Features**:
- 💬 Seamlessly generates engaging and contextually relevant responses.
- 🧠 Fine-tuned for conversational tasks, ensuring natural and fluid interactions.
- 🌟 Employs cutting-edge technologies to deliver state-of-the-art performance.

🔧 **Technical Specifications**:
- 🛠 Architecture: GPT2LMHeadModel
- 📏 Parameters: 24 layers, 2048 hidden size, 16 attention heads
- 🧮 Dropout: Attention dropout of 0.1, embedding dropout of 0.1, and residual dropout of 0.1
- 🎚 Activation Function: GELU (Gaussian Error Linear Unit)
- 📊 Metrics: Achieves outstanding perplexity and accuracy scores

🛠 **Configuration Details**:
- 📝 Task-Specific Parameters: Early stopping, length penalty, beam search, and more to enhance conversational quality.
- 📈 Dynamic Adaptation: Adaptable to changing environmental conditions for optimal performance.
- 📚 Language Support: Primarily English with potential for multilingual applications.

🌟 **Pipeline Tag**: Conversational 🗣️

📚 **Dataset**: Utilizes data from the LDJnr/Capybara dataset 🦙

🔗 **Library and Version**: Transformers v4.37.2 📚

🔑 **License**: Apache-2.0 📜

Get ready to experience the next level of conversational AI with **CustomGPT2Conversational**! 🚀🤖