This model is a fine-tuned version of Babelscape/wikineural-multilingual-ner on the wnut_17 dataset. It achieves the following results on the evaluation set:

Loss: 0.3577
Precision: 0.6570
Recall: 0.4856
F1: 0.5585
Accuracy: 0.9340

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	425	0.3191	0.6465	0.4091	0.5011	0.9273
0.1595	2.0	850	0.3320	0.6719	0.4629	0.5482	0.9316
0.0681	3.0	1275	0.3577	0.6570	0.4856	0.5585	0.9340

Framework versions

Transformers 4.32.1
Pytorch 2.0.1+cu118
Datasets 2.14.4
Tokenizers 0.13.3

TiffanyTiffany/bert-finetuned-ner-Colab

bert-finetuned-ner-Colab

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

TiffanyTiffany/
bert-finetuned-ner-Colab