---
license: mit
base_model: facebookAI/xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: xlm-roberta-large-finetuned-ner
  results: []
---

<!-- 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-ner

This model is a fine-tuned version of [facebookAI/xlm-roberta-large](https://huggingface.co/facebookAI/xlm-roberta-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0433
- Precision: 0.9625
- Recall: 0.9697
- F1: 0.9661
- Accuracy: 0.9916

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2077        | 1.0   | 878  | 0.0604          | 0.9361    | 0.9424 | 0.9392 | 0.9865   |
| 0.0401        | 2.0   | 1756 | 0.0434          | 0.9589    | 0.9647 | 0.9618 | 0.9906   |
| 0.0193        | 3.0   | 2634 | 0.0433          | 0.9625    | 0.9697 | 0.9661 | 0.9916   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2