---
library_name: transformers
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: token_classification_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. -->

# token_classification_NER

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2888
- Precision: 0.5572
- Recall: 0.3837
- F1: 0.4544
- Accuracy: 0.9464

## 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 OptimizerNames.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     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 213  | 0.2756          | 0.6546    | 0.2688 | 0.3811 | 0.9398   |
| No log        | 2.0   | 426  | 0.2604          | 0.5433    | 0.3373 | 0.4162 | 0.9434   |
| 0.1817        | 3.0   | 639  | 0.2846          | 0.5891    | 0.3494 | 0.4386 | 0.9460   |
| 0.1817        | 4.0   | 852  | 0.2784          | 0.5614    | 0.3772 | 0.4512 | 0.9463   |
| 0.0509        | 5.0   | 1065 | 0.2888          | 0.5572    | 0.3837 | 0.4544 | 0.9464   |


### Framework versions

- Transformers 4.53.3
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.21.4