issoh / xwin-finetuned-alpaca-cleaned

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Model's Last Updated: February 07 2024

Introduction of xwin-finetuned-alpaca-cleaned

Model Details of xwin-finetuned-alpaca-cleaned

xwin-finetuned-alpaca-cleaned

This model is a fine-tuned version of TheBloke/Xwin-LM-7B-V0.1-GPTQ on the None dataset.

Model description

More information needed

Intended uses & limitations

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Training and evaluation data

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Training procedure
Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.0002
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • training_steps: 250
Training results
Framework versions
  • Transformers 4.35.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.1

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xwin-finetuned-alpaca-cleaned install

xwin-finetuned-alpaca-cleaned is an open source model from GitHub that offers a free installation service, and any user can find xwin-finetuned-alpaca-cleaned on GitHub to install. At the same time, huggingface.co provides the effect of xwin-finetuned-alpaca-cleaned install, users can directly use xwin-finetuned-alpaca-cleaned installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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Updated:April 29 2025