You can deploy this model and start earning money today!

tillschwoerer/
bert-base-german-cased-gnad10-finetuned-tagesschau-subcategories

Name: bert-base-german-cased-gnad10-finetuned-tagesschau-subcategories
Availability: InStock

generated_from_trainer

laiking/bert-base-german-cased-gnad10

finetune

autotrain_compatible

endpoints_compatible

Views

No views yet

bert-base-german-cased-gnad10-finetuned-tagesschau-subcategories

This model is a fine-tuned version of Mathking/bert-base-german-cased-gnad10 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.4327
Accuracy: 0.8733

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
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.3737	0.4	30	0.9333	0.7133
0.7848	0.8	60	0.5591	0.8133
0.4933	1.2	90	0.4939	0.8
0.3441	1.6	120	0.5537	0.8133
0.3972	2.0	150	0.4229	0.8533
0.2103	2.4	180	0.4327	0.8733
0.1783	2.8	210	0.4834	0.8467
0.1367	3.2	240	0.4634	0.86
0.1273	3.6	270	0.4828	0.8467

Framework versions

Transformers 4.25.1
Pytorch 1.12.1+cu113
Datasets 2.7.1
Tokenizers 0.13.2

tillschwoerer/bert-base-german-cased-gnad10-finetuned-tagesschau-subcategories

bert-base-german-cased-gnad10-finetuned-tagesschau-subcategories

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

tillschwoerer/
bert-base-german-cased-gnad10-finetuned-tagesschau-subcategories