metadata
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: punjabi-roberta-ner
results: []
punjabi-roberta-ner
This model is a fine-tuned version of xlm-roberta-base on an punjabi-ner dataset. It achieves the following results on the evaluation set:
- Loss: 0.0638
- Precision: 0.7625
- Recall: 0.7844
- F1: 0.7733
- Accuracy: 0.9830
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 |
|---|---|---|---|---|---|---|---|
| 0.1017 | 1.0 | 1613 | 0.0739 | 0.7020 | 0.6731 | 0.6872 | 0.9775 |
| 0.0693 | 2.0 | 3226 | 0.0623 | 0.7695 | 0.7433 | 0.7562 | 0.9824 |
| 0.046 | 3.0 | 4839 | 0.0638 | 0.7625 | 0.7844 | 0.7733 | 0.9830 |
Framework versions
- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.14.5
- Tokenizers 0.13.3