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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- wikiann
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: wikiann
type: wikiann
config: ace
split: validation
args: ace
metrics:
- name: Precision
type: precision
value: 0.34523809523809523
- name: Recall
type: recall
value: 0.5420560747663551
- name: F1
type: f1
value: 0.4218181818181818
- name: Accuracy
type: accuracy
value: 0.8688172043010752
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert-finetuned-ner
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the wikiann dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5677
- Precision: 0.3452
- Recall: 0.5421
- F1: 0.4218
- Accuracy: 0.8688
## 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 | 13 | 0.5728 | 0.2077 | 0.3551 | 0.2621 | 0.8199 |
| No log | 2.0 | 26 | 0.5687 | 0.2889 | 0.3645 | 0.3223 | 0.8312 |
| No log | 3.0 | 39 | 0.5447 | 0.2857 | 0.4486 | 0.3491 | 0.8425 |
| No log | 4.0 | 52 | 0.5509 | 0.2881 | 0.4766 | 0.3592 | 0.8489 |
| No log | 5.0 | 65 | 0.5751 | 0.3121 | 0.4579 | 0.3712 | 0.8511 |
| No log | 6.0 | 78 | 0.5358 | 0.3851 | 0.5794 | 0.4627 | 0.8667 |
| No log | 7.0 | 91 | 0.5484 | 0.3491 | 0.5514 | 0.4275 | 0.8645 |
| No log | 8.0 | 104 | 0.5671 | 0.3580 | 0.5421 | 0.4312 | 0.8672 |
| No log | 9.0 | 117 | 0.5666 | 0.3494 | 0.5421 | 0.4249 | 0.8688 |
| No log | 10.0 | 130 | 0.5677 | 0.3452 | 0.5421 | 0.4218 | 0.8688 |
### Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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