metadata
license: mit
tags:
- generated_from_trainer
metrics:
- f1
datasets:
- wikiann
model-index:
- name: xlm-roberta-base-finetuned-panx-all
results:
- task:
type: token-classification
name: Token Classification
dataset:
name: wikiann
type: wikiann
config: en
split: test
metrics:
- name: Accuracy
type: accuracy
value: 0.843189280620875
verified: true
- name: Precision
type: precision
value: 0.8410061269097046
verified: true
- name: Recall
type: recall
value: 0.8568527450211155
verified: true
- name: F1
type: f1
value: 0.8488554853827908
verified: true
- name: loss
type: loss
value: 0.6632214784622192
verified: true
xlm-roberta-base-finetuned-panx-all
This model is a fine-tuned version of xlm-roberta-base on the PAN-X dataset. The model is trained in Chapter 4: Multilingual Named Entity Recognition in the NLP with Transformers book. You can find the full code in the accompanying Github repository.
It achieves the following results on the evaluation set:
- Loss: 0.1739
- F1: 0.8581
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: 5e-05
- train_batch_size: 24
- eval_batch_size: 24
- 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 | F1 |
---|---|---|---|---|
0.2912 | 1.0 | 835 | 0.1883 | 0.8238 |
0.1548 | 2.0 | 1670 | 0.1738 | 0.8480 |
0.101 | 3.0 | 2505 | 0.1739 | 0.8581 |
Framework versions
- Transformers 4.12.0.dev0
- Pytorch 1.9.1+cu102
- Datasets 1.12.1
- Tokenizers 0.10.3