RichardErkhov/mlfoundations-dev_-_dcft_orca-agentinstruct-1M-v1-cleaned-singleturn-gguf

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dcft_orca-agentinstruct-1M-v1-cleaned-singleturn - GGUF

• —Model creator: https://huggingface.co/mlfoundations-dev/
• —Original model: https://huggingface.co/mlfoundations-dev/dcft_orca-agentinstruct-1M-v1-cleaned-singleturn/

Original model description: --- libraryname: transformers license: llama3.1 basemodel: meta-llama/Meta-Llama-3.1-8B tags:

• —llama-factory
• —full
• —generatedfromtrainer model-index:
• —name: dcft_orca-agentinstruct-1M-v1-cleaned-singleturn results: [] ---

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dcft_orca-agentinstruct-1M-v1-cleaned-singleturn

This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B on the mlfoundations-dev/dcft_orca-agentinstruct-1M-v1-cleaned-singleturn dataset. It achieves the following results on the evaluation set:

• —Loss: 0.4835

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: 32
• —gradientaccumulationsteps: 2
• —totaltrainbatch_size: 512
• —totalevalbatch_size: 256
• —optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
• —lrschedulertype: constant
• —lrschedulerwarmup_ratio: 0.1
• —lrschedulerwarmup_steps: 1738
• —num_epochs: 3.0

Training results

Framework versions

• —Transformers 4.46.1
• —Pytorch 2.3.0
• —Datasets 3.0.2
• —Tokenizers 0.20.3