ketchup123 / llama-2-7b-chat-pubmedqa-safeinstruct-num-samples-250

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Model's Last Updated: December 20 2024

Introduction of llama-2-7b-chat-pubmedqa-safeinstruct-num-samples-250

Model Details of llama-2-7b-chat-pubmedqa-safeinstruct-num-samples-250

llama-2-7b-chat-pubmedqa-safeinstruct-num-samples-250

This model is a fine-tuned version of meta-llama/Llama-2-7b-chat-hf on the None dataset.

Model description

More information needed

Intended uses & limitations

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Training and evaluation data

More information needed

Training procedure
Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 5e-05
  • train_batch_size: 4
  • eval_batch_size: 8
  • seed: 3407
  • distributed_type: multi-GPU
  • num_devices: 8
  • total_train_batch_size: 32
  • total_eval_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 5
Training results
Framework versions
  • PEFT 0.13.2
  • Transformers 4.45.2
  • Pytorch 2.4.1+cu121
  • Datasets 3.2.0
  • Tokenizers 0.20.3

Runs of ketchup123 llama-2-7b-chat-pubmedqa-safeinstruct-num-samples-250 on huggingface.co

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llama-2-7b-chat-pubmedqa-safeinstruct-num-samples-250 install

llama-2-7b-chat-pubmedqa-safeinstruct-num-samples-250 is an open source model from GitHub that offers a free installation service, and any user can find llama-2-7b-chat-pubmedqa-safeinstruct-num-samples-250 on GitHub to install. At the same time, huggingface.co provides the effect of llama-2-7b-chat-pubmedqa-safeinstruct-num-samples-250 install, users can directly use llama-2-7b-chat-pubmedqa-safeinstruct-num-samples-250 installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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