metadata
base_model: mor40/BulBERT-ner-bsnlp
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BulBERT-ner-bsnlp
results: []
BulBERT-ner-bsnlp
This model is a fine-tuned version of mor40/BulBERT-ner-bsnlp on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1443
- Precision: 0.7728
- Recall: 0.8862
- F1: 0.8257
- Accuracy: 0.9726
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 91 | 0.1395 | 0.7736 | 0.8690 | 0.8185 | 0.9717 |
| No log | 2.0 | 182 | 0.1386 | 0.7466 | 0.8849 | 0.8099 | 0.9705 |
| No log | 3.0 | 273 | 0.1408 | 0.7695 | 0.8782 | 0.8203 | 0.9726 |
| No log | 4.0 | 364 | 0.1426 | 0.7680 | 0.8851 | 0.8224 | 0.9721 |
| No log | 5.0 | 455 | 0.1443 | 0.7728 | 0.8862 | 0.8257 | 0.9726 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1