---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- wnut_17
model-index:
- name: fine_tune_bert_output
  results: []
---

<!-- 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. -->

# Bertweet-base finetuned on wnut17_ner

This model is a fine-tuned version of [vinai/bertweet-base](https://huggingface.co/vinai/bertweet-base) on the [wnut_17](https://huggingface.co/datasets/wnut_17) dataset.

It achieves the following results on the evaluation set:
- Loss: 0.3239
- Overall Precision: 0.6913
- Overall Recall: 0.5914
- Overall F1: 0.6374
- Overall Accuracy: 0.9499
- Corporation F1: 0.2703
- Creative-work F1: 0.3636
- Group F1: 0.4030
- Location F1: 0.7500
- Person F1: 0.7733
- Product F1: 0.4152

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | Corporation F1 | Creative-work F1 | Group F1 | Location F1 | Person F1 | Product F1 |
|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|:--------------:|:----------------:|:--------:|:-----------:|:---------:|:----------:|
| 0.2691        | 1.0   | 213  | 0.4035          | 0.0               | 0.0            | 0.0        | 0.8979           | 0.0            | 0.0              | 0.0      | 0.0         | 0.0       | 0.0        |
| 0.1604        | 2.0   | 426  | 0.3054          | 0.6255            | 0.4161         | 0.4998     | 0.9324           | 0.0            | 0.0              | 0.0      | 0.3534      | 0.6877    | 0.0        |
| 0.1118        | 3.0   | 639  | 0.2864          | 0.6655            | 0.4643         | 0.5470     | 0.9404           | 0.1961         | 0.1164           | 0.1538   | 0.5803      | 0.7221    | 0.1865     |
| 0.0524        | 4.0   | 852  | 0.2891          | 0.6945            | 0.5042         | 0.5842     | 0.9442           | 0.2017         | 0.3273           | 0.2472   | 0.6522      | 0.7366    | 0.2581     |
| 0.0446        | 5.0   | 1065 | 0.2691          | 0.6815            | 0.5847         | 0.6294     | 0.9486           | 0.2737         | 0.3415           | 0.3007   | 0.6703      | 0.7768    | 0.3243     |
| 0.0296        | 6.0   | 1278 | 0.2739          | 0.6740            | 0.5615         | 0.6126     | 0.9479           | 0.3065         | 0.3766           | 0.3333   | 0.7         | 0.7582    | 0.3472     |
| 0.0261        | 7.0   | 1491 | 0.3150          | 0.6907            | 0.5415         | 0.6071     | 0.9457           | 0.2292         | 0.3350           | 0.304    | 0.6369      | 0.7547    | 0.2982     |
| 0.0193        | 8.0   | 1704 | 0.2922          | 0.6957            | 0.5772         | 0.6310     | 0.9496           | 0.2887         | 0.3621           | 0.3676   | 0.7475      | 0.7645    | 0.4158     |
| 0.0173        | 9.0   | 1917 | 0.2823          | 0.6845            | 0.5963         | 0.6374     | 0.9501           | 0.25           | 0.3863           | 0.3660   | 0.6729      | 0.7810    | 0.4064     |
| 0.0227        | 10.0  | 2130 | 0.2912          | 0.6719            | 0.5681         | 0.6157     | 0.9482           | 0.2268         | 0.3797           | 0.3625   | 0.7045      | 0.7572    | 0.4286     |
| 0.0185        | 11.0  | 2343 | 0.3140          | 0.6941            | 0.5598         | 0.6198     | 0.9482           | 0.2532         | 0.3896           | 0.3382   | 0.7059      | 0.7601    | 0.3961     |
| 0.0221        | 12.0  | 2556 | 0.3527          | 0.6937            | 0.5473         | 0.6119     | 0.9470           | 0.3220         | 0.3687           | 0.35     | 0.7245      | 0.7502    | 0.3308     |
| 0.0099        | 13.0  | 2769 | 0.3332          | 0.6872            | 0.5748         | 0.6260     | 0.9493           | 0.3168         | 0.3782           | 0.3597   | 0.7391      | 0.7627    | 0.4027     |
| 0.0062        | 14.0  | 2982 | 0.3637          | 0.7287            | 0.5465         | 0.6246     | 0.9479           | 0.25           | 0.3700           | 0.4065   | 0.7340      | 0.7526    | 0.3468     |
| 0.0075        | 15.0  | 3195 | 0.3239          | 0.6913            | 0.5914         | 0.6374     | 0.9499           | 0.2703         | 0.3636           | 0.4030   | 0.7500      | 0.7733    | 0.4152     |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.11.0+cu113
- Datasets 2.0.0
- Tokenizers 0.11.6