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More information about previous Neuronovo/neuronovo-9B-v0.2 version available here: 🔗Don't stop DPOptimizing!

Author: Jan KocoÅ„     🔗LinkedIn     🔗Google Scholar     🔗ResearchGate

Changes concerning Neuronovo/neuronovo-9B-v0.2:

  1. Training Dataset: In addition to the Intel/orca_dpo_pairs dataset, this version incorporates a mlabonne/chatml_dpo_pairs. The combined datasets enhance the model's capabilities in dialogues and interactive scenarios, further specializing it in natural language understanding and response generation.

  2. Tokenizer and Formatting: The tokenizer now originates directly from the Neuronovo/neuronovo-9B-v0.2 model.

  3. Training Configuration: The training approach has shifted from using max_steps=200 to num_train_epochs=1. This represents a change in the training strategy, focusing on epoch-based training rather than a fixed number of steps.

  4. Learning Rate: The learning rate has been reduced to a smaller value of 5e-8. This finer learning rate allows for more precise adjustments during the training process, potentially leading to better model performance.

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Datasets used to train Neuronovo/neuronovo-9B-v0.4