metadata
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
datasets:
- skript
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: wikineural-multilingual-ner-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: skript
type: skript
config: myscript
split: train
args: myscript
metrics:
- name: Precision
type: precision
value: 0.9007335298553506
- name: Recall
type: recall
value: 0.9301946902654867
- name: F1
type: f1
value: 0.9152270827528559
- name: Accuracy
type: accuracy
value: 0.9653644982020269
wikineural-multilingual-ner-finetuned-ner
This model is a fine-tuned version of Babelscape/wikineural-multilingual-ner on the skript dataset. It achieves the following results on the evaluation set:
- Loss: 0.1243
- Precision: 0.9007
- Recall: 0.9302
- F1: 0.9152
- Accuracy: 0.9654
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 | 298 | 0.1179 | 0.8975 | 0.8981 | 0.8978 | 0.9592 |
| 0.104 | 2.0 | 596 | 0.1161 | 0.9051 | 0.9201 | 0.9126 | 0.9648 |
| 0.104 | 3.0 | 894 | 0.1243 | 0.9007 | 0.9302 | 0.9152 | 0.9654 |
Framework versions
- Transformers 4.21.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1