RichardErkhov/ondevicellm_-_phi-1_5_sft-gguf

Quantization made by Richard Erkhov.

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phi-15sft - GGUF

• —Model creator: https://huggingface.co/ondevicellm/
• —Original model: https://huggingface.co/ondevicellm/phi-15sft/

Original model description: --- license: mit basemodel: microsoft/phi-15 tags:

• —alignment-handbook
• —trl
• —sft
• —generatedfromtrainer
• —trl
• —sft
• —generatedfromtrainer datasets:
• —HuggingFaceH4/ultrachat_200k model-index:
• —name: phi-15sft 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. -->

phi-15sft

This model is a fine-tuned version of microsoft/phi-1_5 on the HuggingFaceH4/ultrachat_200k dataset. It achieves the following results on the evaluation set:

• —Loss: 1.2542

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: 16
• —evalbatchsize: 8
• —seed: 42
• —distributed_type: multi-GPU
• —num_devices: 4
• —gradientaccumulationsteps: 2
• —totaltrainbatch_size: 128
• —totalevalbatch_size: 32
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: cosine
• —lrschedulerwarmup_steps: 120
• —num_epochs: 3

Training results

Framework versions

• —Transformers 4.37.0
• —Pytorch 2.1.2+cu118
• —Datasets 2.16.1
• —Tokenizers 0.15.0