delphi-adapter

detakarang/delphi-adapter

delphi-adapter is a machine learning model from detakarang. 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 other.

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

Downloads · 30 days

10% of all-time downloads

All-time downloads

Public

Repo size

262 B

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.json2.9 MB · 63%

At a glance

Library: peft
License: other
Access: Public
Created: Dec 25, 2023
Updated: Dec 25, 2023
SHA: d5b3cdc0

Base models

microsoft/phi-2

Model card

From the Hugging Face model README

delphi

This model is a fine-tuned version of microsoft/phi-2 on the alpaca_gpt4_en dataset. It achieves the following results on the evaluation set:

Loss: 0.8625

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-05
train_batch_size: 1
eval_batch_size: 1
seed: 42
distributed_type: multi-GPU
num_devices: 2
gradient_accumulation_steps: 8
total_train_batch_size: 16
total_eval_batch_size: 2
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
num_epochs: 1.0

Training results

Training Loss	Epoch	Step	Validation Loss
1.0325	0.07	200	0.8922
0.9136	0.14	400	0.8801
0.9043	0.21	600	0.8753
0.8903	0.27	800	0.8711
0.9056	0.34	1000	0.8683
0.9001	0.41	1200	0.8673
0.8949	0.48	1400	0.8668
0.8917	0.55	1600	0.8656
0.8951	0.62	1800	0.8648
0.9014	0.68	2000	0.8637
0.8874	0.75	2200	0.8630
0.8968	0.82	2400	0.8628
0.8755	0.89	2600	0.8626
0.9029	0.96	2800	0.8625

Framework versions

PEFT 0.7.1
Transformers 4.36.1
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.15.0

Library: peft
License: other
Created: Dec 25, 2023
Updated: Dec 25, 2023