metadata
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
base_model: dslim/bert-large-NER
model-index:
- name: bert-finetuned-ner-adam
results: []
bert-finetuned-ner-adam
This model is a fine-tuned version of dslim/bert-large-NER on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: nan
- Precision: 0.8340
- Recall: 0.8131
- F1: 0.8234
- Accuracy: 0.9216
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1744 | 1.0 | 893 | nan | 0.8276 | 0.8115 | 0.8195 | 0.9205 |
| 0.128 | 2.0 | 1786 | nan | 0.8404 | 0.8256 | 0.8329 | 0.9238 |
| 0.0768 | 3.0 | 2679 | nan | 0.8340 | 0.8131 | 0.8234 | 0.9216 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2