gemma-ViMMRC-Answer

Angelectronic/gemma-ViMMRC-Answer

gemma-ViMMRC-Answer is a machine learning model from Angelectronic. 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. --

Downloads · 30 days

27% of all-time downloads

All-time downloads

Public

Repo size

422 MB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors200 MB · 90%

At a glance

Library: peft
License: apache-2.0
Access: Public
Created: May 27, 2024
Updated: May 27, 2024
SHA: aa1ae0ca

Base models

unsloth/gemma-1.1-7b-it-bnb-4bit

Model card

From the Hugging Face model README

gemma-ViMMRC-Answer

This model is a fine-tuned version of unsloth/gemma-1.1-7b-it-bnb-4bit on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.1034
Accuracy: 0.8493

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

ViMMRC train and test set

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 5e-05
train_batch_size: 16
eval_batch_size: 8
seed: 3407
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 5
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss
13.1	0.3306	10	5.9870
2.4875	0.6612	20	1.1997
0.5062	0.9917	30	0.2423
0.1602	1.3223	40	0.1251
0.1289	1.6529	50	0.1156
0.1234	1.9835	60	0.1000
0.0727	2.3140	70	0.1068
0.0945	2.6446	80	0.1035
0.0785	2.9752	90	0.1034

Framework versions

PEFT 0.10.0
Transformers 4.40.2
Pytorch 2.3.0
Datasets 2.19.1
Tokenizers 0.19.1

Library: peft
License: apache-2.0
Created: May 27, 2024
Updated: May 27, 2024