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---
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner
results: []
datasets:
- conll2003
language:
- en
library_name: transformers
---
<!-- 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 [CoNLL-2003](https://huggingface.co/datasets/conll2003) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0597
- Precision: 0.9322
- Recall: 0.9482
- F1: 0.9401
- Accuracy: 0.9863
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0793 | 1.0 | 1756 | 0.0771 | 0.9107 | 0.9342 | 0.9223 | 0.9805 |
| 0.0384 | 2.0 | 3512 | 0.0583 | 0.9301 | 0.9455 | 0.9377 | 0.9858 |
| 0.0255 | 3.0 | 5268 | 0.0597 | 0.9322 | 0.9482 | 0.9401 | 0.9863 |
### Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0 |