---
license: cc-by-nc-4.0
base_model: s2w-ai/DarkBERT
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: DarkBERT-finetuned-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. -->

# DarkBERT-finetuned-ner

This model is a fine-tuned version of [s2w-ai/DarkBERT](https://huggingface.co/s2w-ai/DarkBERT) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6416
- Precision: 0.4628
- Recall: 0.5470
- F1: 0.5014
- Accuracy: 0.8901

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 111  | 0.3933          | 0.3563    | 0.4337 | 0.3912 | 0.8726   |
| No log        | 2.0   | 222  | 0.3491          | 0.4345    | 0.5672 | 0.4921 | 0.8886   |
| No log        | 3.0   | 333  | 0.3991          | 0.4284    | 0.5405 | 0.4780 | 0.8795   |
| No log        | 4.0   | 444  | 0.3969          | 0.4565    | 0.5797 | 0.5108 | 0.8877   |
| 0.2744        | 5.0   | 555  | 0.4276          | 0.4737    | 0.5690 | 0.5170 | 0.8887   |
| 0.2744        | 6.0   | 666  | 0.5237          | 0.4918    | 0.5637 | 0.5253 | 0.8862   |
| 0.2744        | 7.0   | 777  | 0.5472          | 0.4855    | 0.5503 | 0.5159 | 0.8877   |
| 0.2744        | 8.0   | 888  | 0.6319          | 0.4581    | 0.5699 | 0.5079 | 0.8855   |
| 0.2744        | 9.0   | 999  | 0.6511          | 0.4901    | 0.5744 | 0.5289 | 0.8901   |
| 0.0627        | 10.0  | 1110 | 0.6758          | 0.4900    | 0.5681 | 0.5262 | 0.8899   |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1