RichardErkhov/HuggingFaceH4_-_starchat2-15b-sft-v0.1-8bits

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starchat2-15b-sft-v0.1 - bnb 8bits

• —Model creator: https://huggingface.co/HuggingFaceH4/
• —Original model: https://huggingface.co/HuggingFaceH4/starchat2-15b-sft-v0.1/

Original model description: --- license: bigcode-openrail-m base_model: bigcode/starcoder2-15b tags:

• —alignment-handbook
• —generatedfromtrainer datasets:
• —HuggingFaceH4/airoboros-3.2
• —HuggingFaceH4/Code-Feedback
• —HuggingFaceH4/orca-math-word-problems-200k
• —HuggingFaceH4/SystemChat
• —HuggingFaceH4/capybara model-index:
• —name: starcoder2-15b-sft-v5.0 results: [] ---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->

Model Card for starchat2-15b-sft-v0.1

This model is a fine-tuned version of bigcode/starcoder2-15b on the HuggingFaceH4/airoboros-3.2, the HuggingFaceH4/Code-Feedback, the HuggingFaceH4/orca-math-word-problems-200k, the HuggingFaceH4/SystemChat and the HuggingFaceH4/capybara datasets. It achieves the following results on the evaluation set:

• —Loss: 0.6614

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• —learning_rate: 2e-05
• —trainbatchsize: 8
• —evalbatchsize: 8
• —seed: 42
• —distributed_type: multi-GPU
• —num_devices: 16
• —totaltrainbatch_size: 128
• —totalevalbatch_size: 128
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: cosine
• —lrschedulerwarmup_ratio: 0.1
• —num_epochs: 3

Training results

Framework versions

• —Transformers 4.39.0.dev0
• —Pytorch 2.1.2+cu121
• —Datasets 2.16.1
• —Tokenizers 0.15.1