hzg – AI Model by jschmock | AlphaNeural AI

You can deploy this model and start earning money today!

jschmock/
hzg

like

0

text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

Views

No views yet

hzg

This model is a fine-tuned version of svalabs/gbert-large-zeroshot-nli on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0046
F1: 1.0

Label-Übersetzungen

0 BHKW
1 Fernwärme
2 Heizkreis_Verbraucher
3 Heizungsanlage_Allgemein
4 Kessel
5 Kreis_Erzeuger(Zubringer)
6 Pufferspeicher
7 Warmwasserbereitung
8 Wärmepumpe
9 Wärmetauscher
10 Wärmeübertrager
11 Zähler

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: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	F1
No log	0.96	17	0.7953	0.7786
No log	1.96	34	0.2800	0.9125
No log	2.96	51	0.0864	0.9929
No log	3.96	68	0.0355	0.9932
No log	4.96	85	0.0093	1.0
No log	5.96	102	0.0348	0.9929
No log	6.96	119	0.0045	1.0
No log	7.96	136	0.0055	1.0
No log	8.96	153	0.0047	1.0
No log	9.96	170	0.0046	1.0

Framework versions

Transformers 4.22.2
Pytorch 1.12.1+cu113
Datasets 2.5.1
Tokenizers 0.12.1