bert-base-multilingual-cased-finetuned-ner
This model is a fine-tuned version of bert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0247
- Precision: 0.9269
- Recall: 0.9509
- F1: 0.9387
- Accuracy: 0.9945
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 |
---|---|---|---|---|---|---|---|
0.0744 | 1.0 | 843 | 0.0266 | 0.8945 | 0.9293 | 0.9116 | 0.9920 |
0.016 | 2.0 | 1686 | 0.0239 | 0.9279 | 0.9446 | 0.9362 | 0.9942 |
0.0075 | 3.0 | 2529 | 0.0247 | 0.9269 | 0.9509 | 0.9387 | 0.9945 |
Framework versions
- Transformers 4.22.1
- Pytorch 1.12.1+cu113
- Datasets 2.5.1
- Tokenizers 0.12.1
- Downloads last month
- 4
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.