pytorch tensorboard distilbert token-classification dataset:conll2003 transformers generated_from_trainer license:apache-2.0 autotrain_compatible
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- conll2003
model_index:
- name: distilbert-base-uncased-finetuned-ner
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: conll2003
      type: conll2003
      args: conll2003
---

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# distilbert-base-uncased-finetuned-ner

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the conll2003 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0623

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.2377        | 1.0   | 878  | 0.0711          |
| 0.0514        | 2.0   | 1756 | 0.0637          |
| 0.031         | 3.0   | 2634 | 0.0623          |


### Framework versions

- Transformers 4.9.0
- Pytorch 1.9.0+cu102
- Datasets 1.10.2
- Tokenizers 0.10.3
