---
library_name: transformers
license: cc-by-4.0
base_model: pczarnik/herbert-base-ner
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: herbert-ner-finetuned
  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. -->

# herbert-ner-finetuned

This model is a fine-tuned version of [pczarnik/herbert-base-ner](https://huggingface.co/pczarnik/herbert-base-ner) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0014
- Precision: 0.9977
- Recall: 0.9982
- F1: 0.9980

## 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
- lr_scheduler_warmup_steps: 327
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Precision | Recall | F1     |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|
| 0.0072        | 0.7634 | 500  | 0.0061          | 0.9697    | 0.9905 | 0.98   |
| 0.0034        | 1.5267 | 1000 | 0.0031          | 0.9879    | 0.9960 | 0.9920 |
| 0.0016        | 2.2901 | 1500 | 0.0017          | 0.9958    | 0.9980 | 0.9969 |
| 0.0012        | 3.0534 | 2000 | 0.0017          | 0.9958    | 0.9975 | 0.9966 |
| 0.0007        | 3.8168 | 2500 | 0.0015          | 0.9976    | 0.9983 | 0.9980 |
| 0.0004        | 4.5802 | 3000 | 0.0015          | 0.9976    | 0.9977 | 0.9977 |
| 0.0006        | 5.3435 | 3500 | 0.0014          | 0.9977    | 0.9982 | 0.9980 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1
- Datasets 2.21.0
- Tokenizers 0.19.1