---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner-word-embedding
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert-finetuned-ner-word-embedding

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the combined training dataset(tweetner7(train_2021)+augmented dataset(train_2021) using word embedding technique).
It achieves the following results on the evaluation set:
- Loss: 0.5502
- Precision: 0.6522
- Recall: 0.4973
- F1: 0.5643
- Accuracy: 0.8615

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.7144        | 1.0   | 624  | 0.5837          | 0.7042    | 0.4422 | 0.5433 | 0.8601   |
| 0.5257        | 2.0   | 1248 | 0.5522          | 0.6575    | 0.4803 | 0.5551 | 0.8610   |
| 0.4564        | 3.0   | 1872 | 0.5502          | 0.6522    | 0.4973 | 0.5643 | 0.8615   |


### Framework versions

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