CharlesLi/llama_2_rlhf_safe_llama_3_70B_default_1000_full
The CharlesLi/llama_2_rlhf_safe_llama_3_70B_default_1000_full model is a 7 billion parameter language model fine-tuned from meta-llama/Llama-2-7b-chat-hf. This model was fine-tuned using a generator dataset, achieving a loss of 0.8687 on its evaluation set. It is based on the Llama 2 architecture and is intended for applications requiring a Llama 2-based model with specific fine-tuning characteristics.
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Model Overview
This model, llama_2_rlhf_safe_llama_3_70B_default_1000_full, is a 7 billion parameter language model derived from the meta-llama/Llama-2-7b-chat-hf base model. It has undergone a specific fine-tuning process using a generator dataset, resulting in an evaluation loss of 0.8687.
Key Training Details
- Base Model: meta-llama/Llama-2-7b-chat-hf
- Parameters: 7 Billion
- Fine-tuning Objective: Generator dataset
- Evaluation Loss: 0.8687
- Hyperparameters:
- Learning Rate: 2e-05
- Optimizer: Adam with betas=(0.9, 0.999) and epsilon=1e-08
- Epochs: 1
- Total Train Batch Size: 32 (across 4 GPUs)
Intended Use Cases
While specific intended uses and limitations are not detailed in the provided information, this model is suitable for developers looking for a Llama 2-7B variant that has been fine-tuned on a generator dataset. Its performance metrics suggest it has learned patterns from this specific dataset, which could be beneficial for tasks aligned with its training data.