---
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-finetuned-core
  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-finetuned-core

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: 0.0000
- Precision: 1.0
- Recall: 1.0
- F1: 1.0

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
| 0.0286        | 1.0   | 434  | 0.0004          | 0.9999    | 0.9999 | 0.9999 |
| 0.0007        | 2.0   | 868  | 0.0001          | 1.0000    | 1.0000 | 1.0000 |
| 0.0002        | 3.0   | 1302 | 0.0001          | 1.0000    | 1.0000 | 1.0000 |
| 0.0002        | 4.0   | 1736 | 0.0000          | 1.0       | 1.0    | 1.0    |
| 0.0001        | 5.0   | 2170 | 0.0000          | 1.0       | 1.0    | 1.0    |
| 0.0001        | 6.0   | 2604 | 0.0000          | 1.0       | 1.0    | 1.0    |
| 0.0001        | 7.0   | 3038 | 0.0000          | 1.0       | 1.0    | 1.0    |
| 0.0001        | 8.0   | 3472 | 0.0000          | 1.0       | 1.0    | 1.0    |


### Framework versions

- Transformers 4.50.3
- Pytorch 2.4.1
- Datasets 2.21.0
- Tokenizers 0.21.1