---
license: apache-2.0
base_model: distilbert-base-cased
tags:
- generated_from_trainer
datasets:
- wikiann
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-base-cased-wikiann
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: wikiann
      type: wikiann
      config: en
      split: validation
      args: en
    metrics:
    - name: Precision
      type: precision
      value: 0.7962710012293402
    - name: Recall
      type: recall
      value: 0.8241905839106461
    - name: F1
      type: f1
      value: 0.8099902737251633
    - name: Accuracy
      type: accuracy
      value: 0.926231747293136
---

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

This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the wikiann dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2549
- Precision: 0.7963
- Recall: 0.8242
- F1: 0.8100
- Accuracy: 0.9262

## 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: 101
- 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 | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.3137        | 1.0   | 1250 | 0.2685          | 0.7716    | 0.8027 | 0.7868 | 0.9181   |
| 0.2199        | 2.0   | 2500 | 0.2526          | 0.7765    | 0.8132 | 0.7944 | 0.9220   |
| 0.1613        | 3.0   | 3750 | 0.2549          | 0.7963    | 0.8242 | 0.8100 | 0.9262   |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.6
- Tokenizers 0.14.1