jk-req

JohanKlingberg/jk-req

jk-req is a machine learning model from JohanKlingberg. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

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Hugging Face

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At a glance

Library: peft
License: apache-2.0
Access: Public
Created: Nov 2, 2024
Updated: Nov 2, 2024
SHA: 4b90a2bf

Base models

TheBloke/Mistral-7B-Instruct-v0.2-GPTQ

Model card

From the Hugging Face model README

jk-req

This model is a fine-tuned version of TheBloke/Mistral-7B-Instruct-v0.2-GPTQ on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.4598

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: 0.0002
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 2
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
1.9818	0.9524	5	1.5863
1.4742	1.9048	10	1.2134
1.1007	2.8571	15	0.9242
0.6604	4.0	21	0.6552
0.5768	4.9524	26	0.5561
0.4812	5.9048	31	0.5101
0.4361	6.8571	36	0.4809
0.3387	8.0	42	0.4651
0.3938	8.9524	47	0.4607
0.3506	9.5238	50	0.4598

Framework versions

PEFT 0.13.2
Transformers 4.44.2
Pytorch 2.5.0+cu121
Datasets 3.1.0
Tokenizers 0.19.1

Library: peft
License: apache-2.0
Created: Nov 2, 2024
Updated: Nov 2, 2024