metadata
library_name: transformers
license: apache-2.0
base_model: mschiesser/ner-bert-german
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: ner_model
results: []
ner_model
This model is a fine-tuned version of mschiesser/ner-bert-german on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3135
- Precision: 0.0517
- Recall: 0.0070
- F1: 0.0123
- Accuracy: 0.9287
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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 0 | 0 | 2.5309 | 0.0 | 0.0 | 0.0 | 0.0171 |
| No log | 1.0 | 5 | 0.4653 | 0.0 | 0.0 | 0.0 | 0.9205 |
| No log | 2.0 | 10 | 0.3807 | 0.0 | 0.0 | 0.0 | 0.9205 |
| No log | 3.0 | 15 | 0.3448 | 0.0323 | 0.0047 | 0.0081 | 0.9269 |
| No log | 4.0 | 20 | 0.3248 | 0.0455 | 0.0070 | 0.0121 | 0.9283 |
| No log | 5.0 | 25 | 0.3135 | 0.0517 | 0.0070 | 0.0123 | 0.9287 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.5.1
- Datasets 3.1.0
- Tokenizers 0.20.2