---
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: mpnet-base-articles-ner
  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. -->

# mpnet-base-articles-ner

This model is a fine-tuned version of [microsoft/mpnet-base](https://huggingface.co/microsoft/mpnet-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8471
- F1: 0.7500

## 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: 5e-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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1.8042        | 1.0   | 5    | 1.6278          | 0.0    |
| 1.5353        | 2.0   | 10   | 1.5332          | 0.0    |
| 1.499         | 3.0   | 15   | 1.4356          | 0.1781 |
| 1.343         | 4.0   | 20   | 1.3254          | 0.3789 |
| 1.2306        | 5.0   | 25   | 1.2572          | 0.5075 |
| 1.1427        | 6.0   | 30   | 1.1572          | 0.5700 |
| 1.0715        | 7.0   | 35   | 1.0875          | 0.6305 |
| 0.9679        | 8.0   | 40   | 1.0261          | 0.6667 |
| 0.9169        | 9.0   | 45   | 0.9924          | 0.6512 |
| 0.8447        | 10.0  | 50   | 0.9457          | 0.7137 |
| 0.8253        | 11.0  | 55   | 0.9216          | 0.7094 |
| 0.7493        | 12.0  | 60   | 0.9068          | 0.7303 |
| 0.7378        | 13.0  | 65   | 0.8896          | 0.7404 |
| 0.7039        | 14.0  | 70   | 0.8827          | 0.7398 |
| 0.7277        | 15.0  | 75   | 0.8632          | 0.7635 |
| 0.6758        | 16.0  | 80   | 0.8517          | 0.775  |
| 0.6642        | 17.0  | 85   | 0.8618          | 0.7449 |
| 0.6327        | 18.0  | 90   | 0.8522          | 0.7490 |
| 0.6238        | 19.0  | 95   | 0.8477          | 0.7500 |
| 0.6101        | 20.0  | 100  | 0.8471          | 0.7500 |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.13.0+cu117
- Datasets 2.6.1
- Tokenizers 0.13.2