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metadata
license: mit
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: bert-base-german-cased-noisy-pretrain-fine-tuned
    results: []

bert-base-german-cased-noisy-pretrain-fine-tuned

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

  • Loss: 0.2925
  • Precision: 0.7933
  • Recall: 0.7457
  • F1: 0.7688
  • Accuracy: 0.9147

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: 7

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 1.0 33 0.3093 0.7456 0.6029 0.6667 0.8808
No log 2.0 66 0.2587 0.7774 0.7286 0.7522 0.9078
No log 3.0 99 0.2529 0.7775 0.7686 0.7730 0.9136
No log 4.0 132 0.2598 0.8063 0.7257 0.7639 0.9147
No log 5.0 165 0.2783 0.7927 0.7429 0.7670 0.9159
No log 6.0 198 0.2899 0.8019 0.74 0.7697 0.9165
No log 7.0 231 0.2925 0.7933 0.7457 0.7688 0.9147

Framework versions

  • Transformers 4.19.2
  • Pytorch 1.11.0+cu113
  • Datasets 2.2.1
  • Tokenizers 0.12.1