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RichardErkhov/mlfoundations-dev_-_hp_ablations_grid_mistral_base-mistralv0.3-gguf

sourceHugging Faceupdated 1y agoView on Hugging Face
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Quantization made by Richard Erkhov.

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hpablationsgridmistralbase-mistralv0.3 - GGUF

  • —Model creator: https://huggingface.co/mlfoundations-dev/
  • —Original model: https://huggingface.co/mlfoundations-dev/hpablationsgridmistralbase-mistralv0.3/

Original model description: --- libraryname: transformers license: apache-2.0 basemodel: mistralai/Mistral-7B-v0.3 tags:

  • —llama-factory
  • —full
  • —generatedfromtrainer model-index:
  • —name: hpablationsgridmistralbase-mistralv0.3 results: [] ---

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hpablationsgridmistralbase-mistralv0.3

This model is a fine-tuned version of mistralai/Mistral-7B-v0.3 on the mlfoundations-dev/oh-dcft-v3-llama3.1-nemotron-70bshareGPTformat dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.0616

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: 5e-06
  • —trainbatchsize: 8
  • —evalbatchsize: 8
  • —seed: 42
  • —distributed_type: multi-GPU
  • —num_devices: 8
  • —gradientaccumulationsteps: 8
  • —totaltrainbatch_size: 512
  • —totalevalbatch_size: 64
  • —optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • —lrschedulertype: constant
  • —num_epochs: 3.0

Training results

Training LossEpochStepValidation Loss
0.45960.99986670.0576
0.36171.999613340.0567
0.26292.999420010.0616

Framework versions

  • —Transformers 4.46.1
  • —Pytorch 2.3.0
  • —Datasets 3.1.0
  • —Tokenizers 0.20.3