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phi-2-instruct

This model is a fine-tuned version of microsoft/phi-2 on the filtered ultrachat200k dataset using the SFT technique.

Model description

More information about the model architecture and specific modifications made during fine-tuning is needed.

Intended uses & limitations

More information about the intended use cases and any limitations of the model is needed.

Training and evaluation data

More information about the datasets used for training and evaluation is needed.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.0002
  • train_batch_size: 4
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9, 0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • training_steps: 51967

Training results

Detailed training results and performance metrics are not provided. It's recommended to reach out to the model creator for more information.

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.15.0
  • Tokenizers 0.15.0

Evaluation and Inference Example

  • For an evaluation of the model and an inference example, refer to the Inference Notebook.

Full Training Metrics on TensorBoard

View the full training metrics on TensorBoard here.

Author's LinkedIn Profile

venkycs

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Inference Examples
Inference API (serverless) does not yet support adapter-transformers models for this pipeline type.

Adapter for

Dataset used to train venkycs/phi-2-instruct