--- language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - llama - trl base_model: unsloth/llama-3-8b-bnb-4bit datasets: - cognitivecomputations/samantha-data --- # Uploaded model - **Developed by:** ruslandev - **License:** apache-2.0 - **Finetuned from model :** unsloth/llama-3-8b-bnb-4bit This model is finetuned on the data of [Samantha](https://erichartford.com/meet-samantha). Prompt format is Alpaca. I used the same system prompt as the original Samantha. ``` """Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request. ### Instruction: {SYSTEM_PROMPT} ### Input: {QUESTION} ### Response: """ ``` # Training [gptchain](https://github.com/RuslanPeresy/gptchain) framework has been used for training. ## Training hyperparameters - learning_rate: 2e-4 - seed: 3407 - gradient_accumulation_steps: 4 - per_device_train_batch_size: 2 - optimizer: adamw_8bit - lr_scheduler_type: linear - warmup_steps: 5 - num_epochs: 2 - weight_decay: 0.01 ## Training results |Training Loss | Epoch | Step | |--------------|-------|------| |2.0778 |0.0 |1 | |0.6255 |0.18 |120 | |0.6208 |0.94 |620 | |0.6244 |2.0 |1306 | 2 epoch finetuning from llama-3-8b took 1 hour on a single A100 with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. [](https://github.com/unslothai/unsloth)