metadata
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: xlm-roberta-base-finetuned-ner
results: []
xlm-roberta-base-finetuned-ner
This model is a fine-tuned version of FacebookAI/xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1709
- Precision: 0.9135
- Recall: 0.9540
- F1: 0.9333
- Accuracy: 0.9703
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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.2034 | 1.0 | 3528 | 0.1751 | 0.8395 | 0.8960 | 0.8668 | 0.9486 |
| 0.1664 | 2.0 | 7056 | 0.1565 | 0.8781 | 0.9253 | 0.9010 | 0.9586 |
| 0.0924 | 3.0 | 10584 | 0.1574 | 0.8903 | 0.9382 | 0.9136 | 0.9643 |
| 0.0641 | 4.0 | 14112 | 0.1663 | 0.9013 | 0.9551 | 0.9274 | 0.9664 |
| 0.0348 | 5.0 | 17640 | 0.1709 | 0.9135 | 0.9540 | 0.9333 | 0.9703 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1