llama3_false_positives_1609_KTO_optimised_model

PaulD/llama3_false_positives_1609_KTO_optimised_model

llama3_false_positives_1609_KTO_optimised_model is a machine learning model from PaulD. 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 llama3.

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

Downloads · 30 days

21% of all-time downloads

All-time downloads

Public

Repo size

54.6 MB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors27.3 MB · 73%

At a glance

Library: peft
License: llama3
Access: Public
Created: Oct 9, 2024
Updated: Oct 10, 2024
SHA: bb5c1d9c

Base models

meta-llama/Meta-Llama-3-8B-Instruct

Model card

From the Hugging Face model README

llama3_false_positives_1609_KTO_optimised_model

This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B-Instruct on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.5894
Eval/rewards/chosen: 2.7219
Eval/logps/chosen: -170.9184
Eval/rewards/rejected: 2.5085
Eval/logps/rejected: -185.9287
Eval/rewards/margins: 0.2134
Eval/kl: 25.1066

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: 0.0001
train_batch_size: 1
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 6.0

Training results

Training Loss	Epoch	Step	Validation Loss
0.4841	0.96	12	0.6000	13.4542
0.1395	2.0	25	0.5894	25.1066

Framework versions

PEFT 0.11.1
Transformers 4.44.0
Pytorch 2.2.0
Datasets 2.20.0
Tokenizers 0.19.1

Library: peft
License: llama3
Created: Oct 9, 2024
Updated: Oct 10, 2024