---
_name_or_path: CustomGPT2ConversationalModel
model_type: gpt2
architectures:
- GPT2LMHeadModel
tokenizer_config:
  bos_token_id: 50256
  eos_token_id: 50256
  n_positions: 2048
  padding_side: left
  truncation_side: right
config:
  activation_function: gelu_new
  attn_pdrop: 0.1
  embd_pdrop: 0.1
  initializer_range: 0.02
  layer_norm_epsilon: 0.00001
  n_ctx: 2048
  n_embd: 2048
  n_head: 16
  n_layer: 36
  n_positions: 2048
  resid_pdrop: 0.1
  vocab_size: 50257
  scale_attn_weights: true
  gradient_checkpointing: true
  use_cache: true
task_specific_params:
  conversational:
    max_length: 1024
    min_length: 20
    temperature: 0.7
    top_k: 40
    top_p: 0.95
    num_beams: 5
    no_repeat_ngram_size: 3
    early_stopping: true
    length_penalty: 2
    do_sample: true
    frequency_penalty: 0.5
    presence_penalty: 0.5
use_cache: true
torch_dtype: float32
transformers_version: 4.37.2
language: en
license: apache-2.0
metrics:
- perplexity
- accuracy
- bleu
tags:
- conversational
- state-of-the-art
---


🎉 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**! 🚀🤖