---
license: apache-2.0
model-index:
- name: TinyNaughtyLlama-v1.0
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: AI2 Reasoning Challenge (25-Shot)
      type: ai2_arc
      config: ARC-Challenge
      split: test
      args:
        num_few_shot: 25
    metrics:
    - type: acc_norm
      value: 35.92
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kevin009/TinyNaughtyLlama-v1.0
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: HellaSwag (10-Shot)
      type: hellaswag
      split: validation
      args:
        num_few_shot: 10
    metrics:
    - type: acc_norm
      value: 61.04
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kevin009/TinyNaughtyLlama-v1.0
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MMLU (5-Shot)
      type: cais/mmlu
      config: all
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 25.82
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kevin009/TinyNaughtyLlama-v1.0
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: TruthfulQA (0-shot)
      type: truthful_qa
      config: multiple_choice
      split: validation
      args:
        num_few_shot: 0
    metrics:
    - type: mc2
      value: 36.77
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kevin009/TinyNaughtyLlama-v1.0
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: Winogrande (5-shot)
      type: winogrande
      config: winogrande_xl
      split: validation
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 60.22
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kevin009/TinyNaughtyLlama-v1.0
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GSM8k (5-shot)
      type: gsm8k
      config: main
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 2.43
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kevin009/TinyNaughtyLlama-v1.0
      name: Open LLM Leaderboard
---

# Model Card for TinyLlama 1.1B

A DPO version of TinyLlama

## Model Information
- **Model Name**: TinyLlama 1.1B Chat
- **Model Version**: 1.0
- **Model Type**: Llama
- **Transformers Version**: 4.35.2
- **Architecture**: LlamaForCausalLM
- **Vocabulary Size**: 32,000
- **Hidden Size**: 2,048
- **Intermediate Size**: 5,632
- **Number of Attention Heads**: 32
- **Number of Hidden Layers**: 22
- **Number of Key-Value Heads**: 4
- **Attention Bias**: False
- **Tie Word Embeddings**: False
- **Max Position Embeddings**: 2,048
- **BOS Token ID**: 1
- **EOS Token ID**: 2
- **Hidden Activation Function**: silu
- **Initializer Range**: 0.02
- **RMS Normalization Epsilon**: 1e-05
- **Rope Scaling**: Not specified
- **Rope Theta**: 10,000.0
- **Torch Data Type**: float16
- **Use Cache**: True

## Overview
Finetunned based on TinyLlama 1.1B Chat is a language model designed for various natural language processing tasks. It utilizes the Llama architecture with a substantial number of hidden layers, attention heads, and a large vocabulary size. The model is trained to generate text in a causal manner, which means it predicts the next word in a sequence based on the preceding context.

## Key Features
- Large vocabulary size of 32,000 words.
- High hidden size (2,048) and intermediate size (5,632) for enhanced modeling capability.
- 32 attention heads for capturing complex relationships in text.
- 22 hidden layers for deep context understanding.
- Utilizes silu (Sigmoid Linear Unit) as the hidden activation function.
- Transformer version 4.35.2.
- Supports cache for faster text generation.

## Pretraining
The model has undergone pretraining with a pretraining task weight of 1.

## Additional Information
- Attention Bias is disabled in this model.
- Word embeddings are not tied.
- Max position embeddings support sequences up to 2,048 tokens.
- RMS normalization epsilon is set to 1e-05.
- Rope scaling and theta are specified as null and 10,000.0, respectively.

## Disclaimer
While this model can generate text, it should be used responsibly and ethically. It may generate inappropriate or biased content, and it is the responsibility of users to filter and moderate the output.

## Model Author
The model is available at TinyLlama/TinyLlama-1.1B-Chat-v1.0.

# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_kevin009__TinyNaughtyLlama-v1.0)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |37.03|
|AI2 Reasoning Challenge (25-Shot)|35.92|
|HellaSwag (10-Shot)              |61.04|
|MMLU (5-Shot)                    |25.82|
|TruthfulQA (0-shot)              |36.77|
|Winogrande (5-shot)              |60.22|
|GSM8k (5-shot)                   | 2.43|