transformers pytorch xlm-roberta token-classification generated_from_trainer license:cc-by-nc-3.0 autotrain_compatible endpoints_compatible region:us
---
license: cc-by-nc-3.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: roberta-large-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. -->

# roberta-large-NER

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1053
- Precision: 0.6030
- Recall: 0.5688
- F1: 0.5854
- Accuracy: 0.9628

## 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: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1188        | 1.0   | 2714 | 0.1053          | 0.6030    | 0.5688 | 0.5854 | 0.9628   |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
