---
tags:
- generated_from_trainer
datasets:
- toydata
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: xlm-roberta-large-ner-hrl-finetuned-ner
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: toydata
      type: toydata
      args: SDN
    metrics:
    - name: Precision
      type: precision
      value: 0.9132452695465905
    - name: Recall
      type: recall
      value: 0.9205854126679462
    - name: F1
      type: f1
      value: 0.9169006511739053
    - name: Accuracy
      type: accuracy
      value: 0.9784804945824268
---

<!-- 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-ner-hrl-finetuned-ner

This model is a fine-tuned version of [Davlan/xlm-roberta-large-ner-hrl](https://huggingface.co/Davlan/xlm-roberta-large-ner-hrl) on the toydata dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0944
- Precision: 0.9132
- Recall: 0.9206
- F1: 0.9169
- Accuracy: 0.9785

## 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 | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 408  | 0.0900          | 0.8508    | 0.9303 | 0.8888 | 0.9719   |
| 0.1087        | 2.0   | 816  | 0.0827          | 0.9043    | 0.9230 | 0.9136 | 0.9783   |
| 0.0503        | 3.0   | 1224 | 0.0944          | 0.9132    | 0.9206 | 0.9169 | 0.9785   |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1