---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- tweetner7
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner-base-model
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: tweetner7
      type: tweetner7
      args: tweetner7
    metrics:
    - name: Precision
      type: precision
      value: 0.6853448275862069
    - name: Recall
      type: recall
      value: 0.6456852791878173
    - name: F1
      type: f1
      value: 0.6649242028227914
    - name: Accuracy
      type: accuracy
      value: 0.8757089711532597
---

<!-- 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-base-model

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the tweetner7 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4160
- Precision: 0.6853
- Recall: 0.6457
- F1: 0.6649
- Accuracy: 0.8757

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 312  | 0.4339          | 0.7365    | 0.5931 | 0.6571 | 0.8731   |
| 0.5311        | 2.0   | 624  | 0.4190          | 0.7348    | 0.6069 | 0.6647 | 0.8763   |
| 0.5311        | 3.0   | 936  | 0.4160          | 0.6853    | 0.6457 | 0.6649 | 0.8757   |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.12.1
- Datasets 2.10.1
- Tokenizers 0.12.1