Hyperledger5Classic_512

YakovElm/Hyperledger5Classic_512

Hyperledger5Classic_512 is a text classification model from YakovElm. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.

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

Downloads · 30 days

8% of all-time downloads

All-time downloads

Public

Repo size

438 MB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.h5438 MB · 100%

At a glance

Task: Text Classification
Library: transformers
License: apache-2.0
Model type: bert
Access: Public
Created: May 27, 2023
Updated: May 27, 2023
SHA: f02cc8ae

Try a prompt

Model card

From the Hugging Face model README

Hyperledger5Classic_512

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

Train Loss: 0.3034
Train Accuracy: 0.8744
Validation Loss: 0.4265
Validation Accuracy: 0.8185
Epoch: 2

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:

optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': 1.0, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': False, 'is_legacy_optimizer': False, 'learning_rate': 3e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
training_precision: float32

Training results

Train Loss	Train Accuracy	Validation Loss	Validation Accuracy	Epoch
0.4068	0.8537	0.4270	0.8361	0
0.3760	0.8537	0.4053	0.8361	1
0.3034	0.8744	0.4265	0.8185	2

Framework versions

Transformers 4.29.2
TensorFlow 2.12.0
Datasets 2.12.0
Tokenizers 0.13.3

Task: Text Classification
Library: transformers
Type: bert
License: apache-2.0
Created: May 27, 2023
Updated: May 27, 2023