metadata
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-finetuned-ner
results: []
bert-base-finetuned-ner
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: 0.3788
- Precision: 0.5395
- Recall: 0.5234
- F1: 0.5313
- Accuracy: 0.9307
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 121 | 0.4099 | 0.2393 | 0.2383 | 0.2388 | 0.8962 |
| No log | 2.0 | 242 | 0.3394 | 0.4340 | 0.3220 | 0.3697 | 0.9180 |
| No log | 3.0 | 363 | 0.2952 | 0.5017 | 0.4170 | 0.4555 | 0.9271 |
| No log | 4.0 | 484 | 0.3419 | 0.5301 | 0.4 | 0.4559 | 0.9284 |
| 0.321 | 5.0 | 605 | 0.3269 | 0.5354 | 0.4723 | 0.5019 | 0.9313 |
| 0.321 | 6.0 | 726 | 0.3382 | 0.5091 | 0.4780 | 0.4931 | 0.9285 |
| 0.321 | 7.0 | 847 | 0.3528 | 0.5489 | 0.5177 | 0.5328 | 0.9315 |
| 0.321 | 8.0 | 968 | 0.3623 | 0.5446 | 0.5191 | 0.5316 | 0.9306 |
| 0.0997 | 9.0 | 1089 | 0.3706 | 0.5225 | 0.5262 | 0.5244 | 0.9283 |
| 0.0997 | 10.0 | 1210 | 0.3788 | 0.5395 | 0.5234 | 0.5313 | 0.9307 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1