RichardErkhov/EEG123_-_subject2-test1-gguf

Quantization made by Richard Erkhov.

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subject2-test1 - GGUF

• —Model creator: https://huggingface.co/EEG123/
• —Original model: https://huggingface.co/EEG123/subject2-test1/

Original model description: --- libraryname: transformers license: llama3.2 basemodel: meta-llama/Llama-3.2-3B tags:

• —alignment-handbook
• —trl
• —sft
• —generatedfromtrainer
• —trl
• —sft
• —generatedfromtrainer datasets:
• —EEG123/DEsubject2 model-index:
• —name: subject2-test1 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. -->

subject2-test1

This model is a fine-tuned version of meta-llama/Llama-3.2-3B on the EEG123/DEsubject2 dataset. It achieves the following results on the evaluation set:

• —Loss: 1.0319

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: 1e-05
• —trainbatchsize: 2
• —evalbatchsize: 2
• —seed: 42
• —distributed_type: multi-GPU
• —num_devices: 4
• —gradientaccumulationsteps: 2
• —totaltrainbatch_size: 16
• —totalevalbatch_size: 8
• —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 4.45.0.dev0
• —Pytorch 2.4.0+cu121
• —Datasets 2.21.0
• —Tokenizers 0.19.1