test_trainer

MaggieZhang/test_trainer

test_trainer is a machine learning model from MaggieZhang. 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

179 KB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors160 KB · 87%

At a glance

Library: peft
License: apache-2.0
Access: Public
Created: Feb 14, 2024
Updated: Feb 14, 2024
SHA: 3d8755db

Base models

Model card

From the Hugging Face model README

test_trainer

This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.3803
Accuracy: 0.842

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 25

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	125	0.6786	0.608
No log	2.0	250	0.6718	0.598
No log	3.0	375	0.6695	0.574
0.6888	4.0	500	0.6583	0.599
0.6888	5.0	625	0.6262	0.684
0.6888	6.0	750	0.5936	0.697
0.6888	7.0	875	0.5520	0.721
0.6057	8.0	1000	0.5149	0.746
0.6057	9.0	1125	0.4848	0.762
0.6057	10.0	1250	0.4558	0.779
0.6057	11.0	1375	0.4346	0.793
0.4583	12.0	1500	0.4215	0.801
0.4583	13.0	1625	0.4094	0.815
0.4583	14.0	1750	0.4027	0.816
0.4583	15.0	1875	0.3962	0.82
0.3847	16.0	2000	0.3926	0.823
0.3847	17.0	2125	0.3873	0.835
0.3847	18.0	2250	0.3857	0.833
0.3847	19.0	2375	0.3823	0.836
0.3565	20.0	2500	0.3819	0.837
0.3565	21.0	2625	0.3850	0.837
0.3565	22.0	2750	0.3806	0.839
0.3565	23.0	2875	0.3801	0.84
0.3348	24.0	3000	0.3808	0.842
0.3348	25.0	3125	0.3803	0.842

Framework versions

PEFT 0.8.2
Transformers 4.38.0.dev0
Pytorch 2.1.0+cu121
Datasets 2.17.0
Tokenizers 0.15.1

Library: peft
License: apache-2.0
Created: Feb 14, 2024
Updated: Feb 14, 2024