metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT-finetuned-ner-S800
results: []
BERT-finetuned-ner-S800
This model is a fine-tuned version of bert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0830
- Precision: 0.5069
- Recall: 0.6662
- F1: 0.5758
- Accuracy: 0.9706
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 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 55 | 0.0873 | 0.4963 | 0.5680 | 0.5298 | 0.9675 |
| No log | 2.0 | 110 | 0.0845 | 0.4948 | 0.6704 | 0.5694 | 0.9693 |
| No log | 3.0 | 165 | 0.0830 | 0.5069 | 0.6662 | 0.5758 | 0.9706 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3