This model is a fine-tuned version of Babelscape/wikineural-multilingual-ner on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0198
Precision: 0.9855
Recall: 0.9833
F1: 0.9844
Accuracy: 0.9956

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: 8
eval_batch_size: 8
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	100	0.1020	0.8658	0.9134	0.8890	0.9693
No log	2.0	200	0.0229	0.9828	0.9821	0.9824	0.9950
No log	3.0	300	0.0198	0.9855	0.9833	0.9844	0.9956

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1

Heyzz/wikineural-finetuned-ner

wikineural-finetuned-ner

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Heyzz/
wikineural-finetuned-ner