mlfoundations-dev/OH_DCFT_V3_wo_slimorca_550k
The mlfoundations-dev/OH_DCFT_V3_wo_slimorca_550k is an 8 billion parameter language model, fine-tuned from Meta's Llama-3.1-8B architecture. This model was trained on the mlfoundations-dev/OH_DCFT_V3_wo_slimorca_550k dataset, achieving a validation loss of 0.6377. It is intended for general language generation tasks, building upon the capabilities of its Llama-3.1 base.
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Overview
This model, mlfoundations-dev/OH_DCFT_V3_wo_slimorca_550k, is a fine-tuned variant of the Meta Llama-3.1-8B base model. It features 8 billion parameters and was trained on a specific dataset, mlfoundations-dev/OH_DCFT_V3_wo_slimorca_550k, to adapt its performance for particular applications.
Training Details
The model underwent training for 3 epochs with a learning rate of 5e-06 and a total batch size of 512 (achieved with a train_batch_size of 8 and gradient_accumulation_steps of 4 across 16 devices). The optimizer used was Adam with standard betas and epsilon, and a constant learning rate scheduler with a 0.1 warmup ratio. During training, the validation loss progressively decreased, reaching 0.6377 by the final epoch.
Potential Use Cases
Given its Llama-3.1-8B foundation, this model is likely suitable for a range of natural language processing tasks, including text generation, summarization, and question answering, especially within domains represented by its fine-tuning dataset. Further evaluation would be needed to determine its specific strengths and limitations.