---
library_name: peft
license: cc-by-4.0
base_model: pczarnik/herbert-base-ner
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: herbert-ner-lora-sensitive
  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-lora-sensitive

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: 0.0070
- Precision: 0.8622
- Recall: 0.8596
- F1: 0.8609

## 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: 0.0002
- 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
| No log        | 1.0   | 315  | 0.0148          | 0.8076    | 0.7253 | 0.7642 |
| 0.1305        | 2.0   | 630  | 0.0096          | 0.8339    | 0.8133 | 0.8234 |
| 0.1305        | 3.0   | 945  | 0.0079          | 0.8538    | 0.8472 | 0.8505 |
| 0.0112        | 4.0   | 1260 | 0.0072          | 0.8556    | 0.8596 | 0.8576 |
| 0.0092        | 5.0   | 1575 | 0.0070          | 0.8622    | 0.8596 | 0.8609 |


### Framework versions

- PEFT 0.12.0
- Transformers 4.50.3
- Pytorch 2.4.1
- Datasets 2.21.0
- Tokenizers 0.21.1