CharlesLi/llama_2_rlhf_safe_llama_3_70B_reflect_500_full
The CharlesLi/llama_2_rlhf_safe_llama_3_70B_reflect_500_full model is a 7 billion parameter language model, fine-tuned from Meta's Llama-2-7b-chat-hf. This model was trained on a generator dataset, achieving a loss of 0.7526 on its evaluation set. It is designed for general language generation tasks, building upon the Llama 2 architecture.
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Model Overview
This model, llama_2_rlhf_safe_llama_3_70B_reflect_500_full, is a 7 billion parameter language model derived from Meta's Llama-2-7b-chat-hf. It has been fine-tuned specifically on a generator dataset, indicating an optimization for text generation tasks.
Key Training Details
During its single epoch of training, the model utilized the following hyperparameters:
- Learning Rate: 2e-05
- Batch Size: 4 (train), 4 (eval)
- Total Batch Size: 32 (train), 16 (eval) with gradient accumulation
- Optimizer: Adam with betas=(0.9, 0.999) and epsilon=1e-08
- Scheduler: Cosine with 0.1 warmup ratio
Performance
The model achieved a loss of 0.7526 on its evaluation set, demonstrating its learning efficacy during the fine-tuning process.
Framework Versions
The training environment included:
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
Potential Use Cases
Given its fine-tuning on a generator dataset, this model is likely suitable for various text generation applications, including but not limited to:
- Content creation
- Dialogue generation
- Creative writing assistance