---
license: apache-2.0
base_model: distilroberta-base
tags:
- generated_from_trainer
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: RoBERTa_conll_epoch_7
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: conll2003
      type: conll2003
      config: conll2003
      split: validation
      args: conll2003
    metrics:
    - name: Precision
      type: precision
      value: 0.944675195215152
    - name: Recall
      type: recall
      value: 0.9569168630090878
    - name: F1
      type: f1
      value: 0.9507566257001923
    - name: Accuracy
      type: accuracy
      value: 0.9885704642385935
---

<!-- 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. -->

# RoBERTa_conll_epoch_7

This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the conll2003 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0772
- Precision: 0.9447
- Recall: 0.9569
- F1: 0.9508
- Accuracy: 0.9886

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.078         | 1.0   | 1756  | 0.0745          | 0.9048    | 0.9310 | 0.9177 | 0.9831   |
| 0.0424        | 2.0   | 3512  | 0.0702          | 0.9317    | 0.9451 | 0.9383 | 0.9851   |
| 0.0254        | 3.0   | 5268  | 0.0722          | 0.9312    | 0.9498 | 0.9404 | 0.9857   |
| 0.0173        | 4.0   | 7024  | 0.0678          | 0.9348    | 0.9505 | 0.9426 | 0.9867   |
| 0.0086        | 5.0   | 8780  | 0.0798          | 0.9306    | 0.9498 | 0.9401 | 0.9859   |
| 0.0058        | 6.0   | 10536 | 0.0786          | 0.9406    | 0.9562 | 0.9483 | 0.9881   |
| 0.0033        | 7.0   | 12292 | 0.0772          | 0.9447    | 0.9569 | 0.9508 | 0.9886   |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1