---
library_name: transformers
base_model: FacebookAI/xlm-roberta-large-finetuned-conll03-english
tags:
- generated_from_trainer
datasets:
- biobert_json
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: xlm-roberta-large-finetuned-conll03-english-finetuned-ner
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: biobert_json
      type: biobert_json
      config: Biobert_json
      split: validation
      args: Biobert_json
    metrics:
    - name: Precision
      type: precision
      value: 0.947671764437343
    - name: Recall
      type: recall
      value: 0.9724776014522457
    - name: F1
      type: f1
      value: 0.9599144533394989
    - name: Accuracy
      type: accuracy
      value: 0.9809696788972173
---

<!-- 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. -->

# xlm-roberta-large-finetuned-conll03-english-finetuned-ner

This model is a fine-tuned version of [FacebookAI/xlm-roberta-large-finetuned-conll03-english](https://huggingface.co/FacebookAI/xlm-roberta-large-finetuned-conll03-english) on the biobert_json dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0876
- Precision: 0.9477
- Recall: 0.9725
- F1: 0.9599
- Accuracy: 0.9810

## 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 | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.255         | 1.0   | 612  | 0.0956          | 0.9305    | 0.9638 | 0.9468 | 0.9749   |
| 0.0997        | 2.0   | 1224 | 0.0871          | 0.9397    | 0.9740 | 0.9565 | 0.9795   |
| 0.0711        | 3.0   | 1836 | 0.0848          | 0.9474    | 0.9718 | 0.9595 | 0.9806   |
| 0.0552        | 4.0   | 2448 | 0.0860          | 0.9464    | 0.9744 | 0.9602 | 0.9808   |
| 0.0354        | 5.0   | 3060 | 0.0876          | 0.9477    | 0.9725 | 0.9599 | 0.9810   |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3