ner-2-roberta-base
This model is a fine-tuned version of roberta-base on the lltala/e-ner-roberta-base dataset. It achieves the following results on the evaluation set:
- Loss: 0.0798
- Loc Precision: 0.625
- Loc Recall: 0.7216
- Loc F1: 0.6699
- Loc Number: 97
- Org Precision: 0.8401
- Org Recall: 0.6716
- Org F1: 0.7465
- Org Number: 673
- Per Precision: 0.9425
- Per Recall: 0.9762
- Per F1: 0.9591
- Per Number: 84
- Overall Precision: 0.8195
- Overall Recall: 0.7073
- Overall F1: 0.7593
- Overall Accuracy: 0.9854
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: 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: 3.0
Training results
Framework versions
- Transformers 4.35.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
- Downloads last month
- 2
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.