README.md

---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner
  results:
  - task:
      type: token-classification
      name: Token Classification
    dataset:
      name: conll2003
      type: conll2003
      config: conll2003
      split: validation
      args: conll2003
    metrics:
    - type: precision
      value: 0.9316493313521546
      name: Precision
    - type: recall
      value: 0.9496802423426456
      name: Recall
    - type: f1
      value: 0.9405783815317944
      name: F1
    - type: accuracy
      value: 0.9861806087007712
      name: Accuracy
  - task:
      type: token-classification
      name: Token Classification
    dataset:
      name: conll2003
      type: conll2003
      config: conll2003
      split: test
    metrics:
    - type: accuracy
      value: 0.8996864215817588
      name: Accuracy
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNWJkMzFiYTc0YzI3MGRiOGQ0MTA0OTgwYmQ3ODU2ZTk5MGQ5NGQwYjViMzhiZWFjNzUyMmYxM2QxOTQ5ZTI0MyIsInZlcnNpb24iOjF9.SECjYrUHXW-IJZPqjPMM15PAItaCHQKynFjkmu3cXj2wvUh-O_mvAvaqq3fLJSyNQfPyImRc89_gusSsgGD8Aw
    - type: precision
      value: 0.9290522347872914
      name: Precision
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiOTdhNzkwYTMzYzE0NzdkNzc0ODQ4NmYwNTVjOGI1ZGQ3YmZlNmJjNzEwNDFiOWZiMGMxYTM1YTIxNGVkMTc2NyIsInZlcnNpb24iOjF9.imy5h8_PQmOLSWZx341f_VdLqaXSUfgmnvBtq8r5l-tc9BbzUqdl5TiyxLyqOt0JFO0lQooirG1YxivynmesBw
    - type: recall
      value: 0.9153430381006068
      name: Recall
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYzY5M2E3ZDc4NWFkNGFkOWY1Mzk3YzIyYzg0Y2U0NzM1ZWRkNjczM2QyODdkMTg5MDhlZDMwOThhMTA3NGFlYSIsInZlcnNpb24iOjF9.8aVjcW3T8W4a9LiEAgakRM_kechC9xK51nAl3SxypmES6MNxVjsYCD8wvxPF7ddgmTCB0vyCTeelgT6HuGhtCQ
    - type: auc
      value: NaN
      name: AUC
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMmQ0ZTk4ZWJmNmU4M2U1OTNiZGMyNmNmYmJmMzMwZjQ4MDRlYmYxOWJjNTM0N2FjMWExNGI1ZTVmN2I2MGZhOSIsInZlcnNpb24iOjF9.0B6-aHCUx_SdHfSTlcXlVh8mE3gQe7L2Dk2-RyLp7a3YUzOhJNAj--Bz0I5lGH0m7PffPwBuZpccdnFJfg_WAg
    - type: f1
      value: 0.9221466869331375
      name: F1
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZDk1ZWY1MTVhYTZmYzNhYmZkNjdiNjNjMTk0OGMzNzQzMmE0MGI4NTc5YmViZTg3NDQ2MjE1YzNkZDUwZTc4NSIsInZlcnNpb24iOjF9.ZlDFXSg8DZL3KLeU3liwZYWgpF1wrTieUYTVg9lVkgYb7A5jlCcgT4X3LqXCScaIt84BS_6-eqNHV_ukJiUUAQ
    - type: loss
      value: 0.8573787212371826
      name: loss
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNjY0OWJmZWI5ZTA5ODIzYzE5YmFkZmQ2OTIwOTJlNDU4ZmUyZDFlYTU1MmRjODRlMWZlMmMyYjUwNmQyYzhmNCIsInZlcnNpb24iOjF9.mCnEvOsb3-HlTzhiY7kboe1rCD8ikdyKgEPMixST1qbGoTmfff0ZclZL9Sjz46MREnLYNgPr_whSEzvMWC3aAw
---

<!-- 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 conll2003 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0630
- Precision: 0.9316
- Recall: 0.9497
- F1: 0.9406
- Accuracy: 0.9862

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0885        | 1.0   | 1756 | 0.0692          | 0.9162    | 0.9312 | 0.9236 | 0.9813   |
| 0.0364        | 2.0   | 3512 | 0.0652          | 0.9233    | 0.9455 | 0.9342 | 0.9854   |
| 0.018         | 3.0   | 5268 | 0.0630          | 0.9316    | 0.9497 | 0.9406 | 0.9862   |


### Framework versions

- Transformers 4.27.4
- Pytorch 2.0.0+cu117
- Datasets 2.11.0
- Tokenizers 0.13.3