license: mit
tags:
- generated_from_trainer
base_model: Josephgflowers/TinyLlama-Cinder-Tiny-Agent
model-index:
- name: TinyLlama-Cinder-Agent-v1
results: []
The goal of this Model is to build a Tinyllama model that can be used for tool usage, RAG, take system instructions, and as a general assistant.
This model is a fine-tuned version of Josephgflowers/TinyLlama-Cinder-Tiny-Agent.
Special Thanks to https://nationtech.io/ for their generous sponorship in training this model.
This model is a fine-tuned version of Josephgflowers/TinyLlama-3T-Cinder-v1.2 on https://huggingface.co./datasets/Josephgflowers/agent_1.
Model description
This models is trained for RAG, Summary, Function Calling and Tool usage. Trained off of Cinder. Cinder is a chatbot designed for chat about STEM topics and storytelling. More information coming.
See https://huggingface.co./Josephgflowers/TinyLlama-Cinder-Agent-Rag/blob/main/tinyllama_agent_cinder_txtai-rag.py For usage example with wiki rag.
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 12
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1.0
- mixed_precision_training: Native AMP
Training results
Framework versions
- Transformers 4.41.0.dev0
- Pytorch 2.2.2+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 39.17 |
| AI2 Reasoning Challenge (25-Shot) | 34.90 |
| HellaSwag (10-Shot) | 53.87 |
| MMLU (5-Shot) | 26.89 |
| TruthfulQA (0-shot) | 39.08 |
| Winogrande (5-shot) | 59.12 |
| GSM8k (5-shot) | 21.15 |