metadata
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-german-cased-own-data-ner
results: []
bert-base-german-cased-own-data-ner
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: 0.0456
- Precision: 0.7190
- Recall: 0.85
- F1: 0.7791
- Accuracy: 0.9904
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 0.8 | 32 | 0.0442 | 0.8066 | 0.7893 | 0.7978 | 0.9903 |
| No log | 1.6 | 64 | 0.0435 | 0.7337 | 0.8464 | 0.7861 | 0.9884 |
| No log | 2.4 | 96 | 0.0366 | 0.7702 | 0.85 | 0.8081 | 0.9909 |
| No log | 3.2 | 128 | 0.0389 | 0.7697 | 0.8357 | 0.8014 | 0.9907 |
| No log | 4.0 | 160 | 0.0377 | 0.7664 | 0.8321 | 0.7979 | 0.9911 |
| No log | 4.8 | 192 | 0.0456 | 0.7190 | 0.85 | 0.7791 | 0.9904 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.9.0+cu111
- Datasets 2.1.0
- Tokenizers 0.12.1