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: 0.0475
- Precision: 0.7476
- Recall: 0.8464
- F1: 0.7940
- Accuracy: 0.9908
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 160 | 0.0497 | 0.6704 | 0.8643 | 0.7551 | 0.9870 |
| No log | 2.0 | 320 | 0.0370 | 0.7912 | 0.8393 | 0.8146 | 0.9924 |
| No log | 3.0 | 480 | 0.0443 | 0.7660 | 0.8536 | 0.8074 | 0.9910 |
| 0.0585 | 4.0 | 640 | 0.0475 | 0.7476 | 0.8464 | 0.7940 | 0.9908 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.9.0+cu111
- Datasets 2.1.0
- Tokenizers 0.12.1