metadata
base_model: dbmdz/bert-large-cased-finetuned-conll03-english
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: large-bert-cased-ner-finetuned-wikineural-final
results: []
large-bert-cased-ner-finetuned-wikineural-final
This model is a fine-tuned version of dbmdz/bert-large-cased-finetuned-conll03-english on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0473
- Precision: 0.9055
- Recall: 0.9156
- F1: 0.9105
- Accuracy: 0.9860
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: 9
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.04 | 1.0 | 10321 | 0.0473 | 0.9055 | 0.9156 | 0.9105 | 0.9860 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1