RichardErkhov/klcsp_-_mistral7b-fft-summarization-11-v1-gguf

Quantization made by Richard Erkhov.

Github

Discord

Request more models

mistral7b-fft-summarization-11-v1 - GGUF

• —Model creator: https://huggingface.co/klcsp/
• —Original model: https://huggingface.co/klcsp/mistral7b-fft-summarization-11-v1/

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

• —trl
• —sft
• —generatedfromtrainer datasets:
• —generator model-index:
• —name: mistral7b-fft-summarization-11-v1 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. -->

mistral7b-fft-summarization-11-v1

This model is a fine-tuned version of mistralai/Mistral-7B-v0.3 on the generator dataset. It achieves the following results on the evaluation set:

• —Loss: 2.0332

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: 16
• —seed: 42
• —distributed_type: multi-GPU
• —num_devices: 8
• —gradientaccumulationsteps: 4
• —totaltrainbatch_size: 512
• —totalevalbatch_size: 128
• —optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
• —lrschedulertype: cosine
• —lrschedulerwarmup_ratio: 0.1
• —num_epochs: 1

Training results

Framework versions

• —Transformers 4.46.3
• —Pytorch 2.3.1+cu121
• —Datasets 3.1.0
• —Tokenizers 0.20.3