metadata
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-multilingual-cased-finetuned-ner
results: []
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: 0.1601
- Precision: 0.8875
- Recall: 0.9009
- F1: 0.8942
- Accuracy: 0.9720
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 |
|---|---|---|---|---|---|---|---|
| 0.1977 | 1.0 | 878 | 0.0664 | 0.9216 | 0.9346 | 0.9280 | 0.9828 |
| 0.0473 | 2.0 | 1756 | 0.0579 | 0.9491 | 0.9473 | 0.9482 | 0.9871 |
| 0.0278 | 3.0 | 2634 | 0.0549 | 0.9544 | 0.9546 | 0.9545 | 0.9885 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0