metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: bert-finetuned-ner
results: []
bert-finetuned-ner
This model is a fine-tuned version of bert-base-uncased on an unknown dataset.
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: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | B-location-precision | B-location-recall | B-location-f1 | I-location-precision | I-location-recall | I-location-f1 | B-group-precision | B-group-recall | B-group-f1 | I-group-precision | I-group-recall | I-group-f1 | B-corporation-precision | B-corporation-recall | B-corporation-f1 | I-corporation-precision | I-corporation-recall | I-corporation-f1 | B-person-precision | B-person-recall | B-person-f1 | I-person-precision | I-person-recall | I-person-f1 | B-creative-work-precision | B-creative-work-recall | B-creative-work-f1 | I-creative-work-precision | I-creative-work-recall | I-creative-work-f1 | B-product-precision | B-product-recall | B-product-f1 | I-product-precision | I-product-recall | I-product-f1 | Corporation-precision | Corporation-recall | Corporation-f1 | Corporation-number | Creative-work-precision | Creative-work-recall | Creative-work-f1 | Creative-work-number | Group-precision | Group-recall | Group-f1 | Group-number | Location-precision | Location-recall | Location-f1 | Location-number | Person-precision | Person-recall | Person-f1 | Person-number | Product-precision | Product-recall | Product-f1 | Product-number |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 425 | 0.1275 | 0.5171 | 0.3838 | 0.4406 | 0.9687 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | 0.0 | 0.0 | 0.0 | 221 | 0.0 | 0.0 | 0.0 | 140 | 0.0 | 0.0 | 0.0 | 264 | 0.4054 | 0.4690 | 0.4349 | 548 | 0.6234 | 0.7348 | 0.6745 | 660 | 0.2963 | 0.1127 | 0.1633 | 142 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cpu
- Datasets 2.14.6
- Tokenizers 0.14.1