metadata
base_model: FacebookAI/xlm-roberta-large-finetuned-conll03-english
tags:
- generated_from_trainer
datasets:
- conll2002
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: xml-roberta-large-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: conll2002
type: conll2002
config: es
split: validation
args: es
metrics:
- name: Precision
type: precision
value: 0.880600409370025
- name: Recall
type: recall
value: 0.8897058823529411
- name: F1
type: f1
value: 0.8851297291118985
- name: Accuracy
type: accuracy
value: 0.9806463992982264
xml-roberta-large-finetuned-ner
This model is a fine-tuned version of FacebookAI/xlm-roberta-large-finetuned-conll03-english on the conll2002 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1364
- Precision: 0.8806
- Recall: 0.8897
- F1: 0.8851
- Accuracy: 0.9806
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0743 | 1.0 | 2081 | 0.1131 | 0.8385 | 0.8587 | 0.8485 | 0.9771 |
| 0.049 | 2.0 | 4162 | 0.1429 | 0.8492 | 0.8564 | 0.8528 | 0.9756 |
| 0.031 | 3.0 | 6243 | 0.1298 | 0.8758 | 0.8817 | 0.8787 | 0.9800 |
| 0.0185 | 4.0 | 8324 | 0.1279 | 0.8827 | 0.8890 | 0.8859 | 0.9808 |
| 0.0125 | 5.0 | 10405 | 0.1364 | 0.8806 | 0.8897 | 0.8851 | 0.9806 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.19.1