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bert-base-german-cased-finetuned-subj_preTrained_with_noisyData – AI Model by tbosse | AlphaNeural AI
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tbosse
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bert-base-german-cased-finetuned-subj_preTrained_with_noisyData
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transformers
pytorch
tensorboard
bert
token-classification
generated_from_trainer
mit
autotrain_compatible
endpoints_compatible
us
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bert-base-german-cased-finetuned-subj_preTrained_with_noisyData
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: 0.0192
Precision: 0.9203
Recall: 0.8703
F1: 0.8946
Accuracy: 0.9939
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
No log
1.0
245
0.0258
0.9172
0.7990
0.8540
0.9918
No log
2.0
490
0.0192
0.9203
0.8703
0.8946
0.9939
Framework versions
Transformers 4.19.1
Pytorch 1.11.0+cu113
Datasets 2.2.1
Tokenizers 0.12.1
