RichardErkhov/taicheng_-_zephyr-7b-align-scan-3e-07-0.62-polynomial-3.0-gguf

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zephyr-7b-align-scan-3e-07-0.62-polynomial-3.0 - GGUF

• —Model creator: https://huggingface.co/taicheng/
• —Original model: https://huggingface.co/taicheng/zephyr-7b-align-scan-3e-07-0.62-polynomial-3.0/

Original model description: --- libraryname: transformers license: apache-2.0 basemodel: alignment-handbook/zephyr-7b-sft-full tags:

• —alignment-handbook
• —trl
• —dpo
• —generatedfromtrainer
• —trl
• —dpo
• —generatedfromtrainer datasets:
• —HuggingFaceH4/ultrafeedback_binarized model-index:
• —name: zephyr-7b-align-scan-3e-07-0.62-polynomial-3.0 results: [] ---

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zephyr-7b-align-scan-3e-07-0.62-polynomial-3.0

This model is a fine-tuned version of alignment-handbook/zephyr-7b-sft-full on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:

• —Loss: 0.8726
• —Rewards/chosen: -0.1874
• —Rewards/rejected: -1.8304
• —Rewards/accuracies: 0.375
• —Rewards/margins: 1.6430
• —Logps/rejected: -84.0806
• —Logps/chosen: -74.7935
• —Logits/rejected: -2.6285
• —Logits/chosen: -2.6453

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: 3e-07
• —trainbatchsize: 8
• —evalbatchsize: 8
• —seed: 42
• —distributed_type: multi-GPU
• —num_devices: 4
• —gradientaccumulationsteps: 2
• —totaltrainbatch_size: 64
• —totalevalbatch_size: 32
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: polynomial
• —lrschedulerwarmup_ratio: 0.1
• —num_epochs: 3

Training results

Framework versions

• —Transformers 4.44.2
• —Pytorch 2.4.0
• —Datasets 2.21.0
• —Tokenizers 0.19.1