---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-ner-conll2003
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilbert-ner-conll2003

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0131
- Accuracy: 0.9965

## 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 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 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0825        | 1.0   | 878  | 0.0111          | 0.9968   |
| 0.0075        | 2.0   | 1756 | 0.0092          | 0.9973   |
| 0.0041        | 3.0   | 2634 | 0.0093          | 0.9975   |
| 0.0027        | 4.0   | 3512 | 0.0097          | 0.9975   |
| 0.0021        | 5.0   | 4390 | 0.0099          | 0.9975   |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3