GPC_Class_Classificator_Food – AI Model by sianbrumm | AlphaNeural AI | AlphaNeural AI

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sianbrumm/
GPC_Class_Classificator_Food

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dbmdz/bert-base-german-uncased

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class_classificator_results

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

Loss: 0.7191
Precision: 0.9280
Recall: 0.9280
F1: 0.9280
Accuracy: 0.9280

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: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 6

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
1.3487	1.0	2527	1.1844	0.8355	0.8355	0.8355	0.8355
0.9081	2.0	5054	0.9115	0.8897	0.8897	0.8897	0.8897
0.6327	3.0	7581	0.7873	0.9038	0.9038	0.9038	0.9038
0.3874	4.0	10108	0.7599	0.9196	0.9196	0.9196	0.9196
0.2643	5.0	12635	0.7191	0.9280	0.9280	0.9280	0.9280
0.2146	6.0	15162	0.7315	0.9300	0.9300	0.9300	0.9300

Framework versions

Transformers 4.41.2
Pytorch 2.0.1+cu117
Datasets 2.20.0
Tokenizers 0.19.1