metadata
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: punjabi-bert-ner
results: []
punjabi-bert-ner
This model is a fine-tuned version of bert-base-multilingual-cased on an punjabi-ner dataset. It achieves the following results on the evaluation set:
- Loss: 0.0773
- Precision: 0.7730
- Recall: 0.7767
- F1: 0.7748
- Accuracy: 0.9794
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 |
|---|---|---|---|---|---|---|---|
| 0.1001 | 1.0 | 1613 | 0.0792 | 0.7619 | 0.6539 | 0.7037 | 0.9752 |
| 0.0645 | 2.0 | 3226 | 0.0742 | 0.7684 | 0.7528 | 0.7605 | 0.9787 |
| 0.0397 | 3.0 | 4839 | 0.0773 | 0.7730 | 0.7767 | 0.7748 | 0.9794 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3