---
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-NER
  results: []
datasets:
- conll2003
language:
- en
pipeline_tag: token-classification
---

<!-- 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. -->

# distilbert-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: 0.0649
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.9838

## 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: 5e-05
- train_batch_size: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1  | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|
| No log        | 0.91  | 200  | 0.0681          | 0.0       | 0.0    | 0.0 | 0.9805   |
| No log        | 1.82  | 400  | 0.0599          | 0.0       | 0.0    | 0.0 | 0.9827   |
| 0.1171        | 2.73  | 600  | 0.0641          | 0.0       | 0.0    | 0.0 | 0.9834   |
| 0.1171        | 3.64  | 800  | 0.0652          | 0.0       | 0.0    | 0.0 | 0.9843   |
| 0.0177        | 4.55  | 1000 | 0.0649          | 0.0       | 0.0    | 0.0 | 0.9838   |


### Framework versions

- Transformers 4.39.1
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2