bert-base-german-cased-finetuned-subj_preTrained_with_noisyData_v2

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

• Loss: 0.0074
• Precision: 0.9776
• Recall: 0.9593
• F1: 0.9683
• Accuracy: 0.9981

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: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.038	1.0	625	0.0091	0.9694	0.9426	0.9559	0.9974
0.0079	2.0	1250	0.0074	0.9776	0.9593	0.9683	0.9981

Framework versions

• Transformers 4.19.2
• Pytorch 1.11.0+cu113
• Datasets 2.2.2
• Tokenizers 0.12.1