---
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
      args: conll2003
    metrics:
    - type: precision
      value: 0.9329581195166363
      name: Precision
    - type: recall
      value: 0.9485021878155503
      name: Recall
    - type: f1
      value: 0.9406659434198448
      name: F1
    - type: accuracy
      value: 0.985356449049273
      name: Accuracy
  - task:
      type: token-classification
      name: Token Classification
    dataset:
      name: conll2003
      type: conll2003
      config: conll2003
      split: test
    metrics:
    - type: accuracy
      value: 0.8998282409668931
      name: Accuracy
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZGY2OWQ3ZjUzMjU1NjE0NmNjOTBjNzU4ZTMwOTk5Yjg3M2JiZWEyMTA4NmRmNmZmYTM4NTQ0MWQ2M2M2ZmFiMSIsInZlcnNpb24iOjF9.W_zZkhiwURr4s02RHmlqvhPBNSG203Rg0r19bOX-V7hptvJ5PPOmlf8812-mr8n3OzbtBOUtSyQ1GqEfwLruDg
    - type: precision
      value: 0.9289800450920349
      name: Precision
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiN2VmY2UxZWI4NTRlMWM2ZWRmOTJmZWY4MWIzM2ZlNTg2ZmVkOTcyZWNhMjM4ZGMwNmJiNWJhMzRlMzcwOGE5YyIsInZlcnNpb24iOjF9.l2N76E2Z1BIpgpZW2ftwnwK3XWOcum7B_2rOKV3jHuz5jNxsRJE1ijEciycVz4LcpmR_uCeXMgP635y7ANxhBg
    - type: recall
      value: 0.915425937593262
      name: Recall
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNGNjNGQxZThhNDdmZTg4MWQ0OWE2NmVkM2E4ZTliNDkyZjVlOGU1ZjhlNzU3MDdlYTYxZGYyNmFkYTQxOTg0MiIsInZlcnNpb24iOjF9.mpenw6Oc9jWHYMhcA9iQq9vNEXEyp7SFcw5OpoYM-VSBDhTE6ls2Bis31wuiK5_J6iAsdz4-WRFqF4D5NuwRDw
    - type: auc
      value: NaN
      name: AUC
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNWI3NDVjYTZjNGIwNWJmNjUxNmFmZWFlZjgxNTQ2MmIyZTgyNDdkNDEzZTA3YTAwYTUyOGRkYzI1OGU5ZjNmMCIsInZlcnNpb24iOjF9.2GTBzDgINbkOHql9ubKt-yTYIhqdUdqCy7dyO6qtRKy5f0RqciGljbDF60rEi2Kk1oy3s0rogy7IyN04LTp1BA
    - type: f1
      value: 0.9221531883622275
      name: F1
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMDQ3M2JlNTQ1ZTIzMjM2ODVjMDJlZmMzZTQ0ODE1ZTQ3Yzc5OTMzYzkxMDZjNzJkNDE3Y2NlZTJiYTE3YTI2MyIsInZlcnNpb24iOjF9.rw7QYqH-Nl5LcRPMkjRTwpL6a39vO-aM8ByQdH5cNwEdAnJWnXmfO0sLbwufv8AI1A0JyDjQ5NAsQA5JZLiFCg
    - type: loss
      value: 0.8484721779823303
      name: loss
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYWZlZWI5NjUxYzdiZTNiOGE5ZWZhMDZiMDQ2ZjY3ZmEwZTFiYzFlYjQwZWViNmE0NmRhNWU2NjlmMzVjYjhkOSIsInZlcnNpb24iOjF9.Y8ANGfc1yDhHe0vGbYiGd4qJvnqymfwQZipf7kn9HOnGM6MXA0hz3X4IBUBwy0sKEffDGsTDredPrMICVF6nAg
---

<!-- 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: 0.0649
- Precision: 0.9330
- Recall: 0.9485
- F1: 0.9407
- Accuracy: 0.9854

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0871        | 1.0   | 1756 | 0.0672          | 0.9209    | 0.9387 | 0.9297 | 0.9834   |
| 0.0394        | 2.0   | 3512 | 0.0584          | 0.9311    | 0.9505 | 0.9407 | 0.9857   |
| 0.0201        | 3.0   | 5268 | 0.0649          | 0.9330    | 0.9485 | 0.9407 | 0.9854   |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1