Downloads · 30 days
5
2% of all-time downloads
xlm-roberta-base-WNUT-ner
dmargutierrez/xlm-roberta-base-WNUT-ner
xlm-roberta-base-WNUT-ner is a token classification model from dmargutierrez. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
All-time downloads
254
Public
Repo size
11.1 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin1.1 GB · 98%
At a glance
- Task
- Token Classification
- Library
- transformers
- License
- mit
- Model type
- xlm-roberta
- Access
- Public
- Created
- Mar 14, 2023
- Updated
- Mar 14, 2023
- SHA
- 096af0cb
Try a prompt
Datasets
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
xlm-roberta-base-WNUT-ner
This model is a fine-tuned version of xlm-roberta-base on the wnut_17 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3376
- Precision: 0.6252
- Recall: 0.4791
- F1: 0.5425
- Accuracy: 0.9523
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 213 | 0.2787 | 0.5650 | 0.3383 | 0.4232 | 0.9418 |
| No log | 2.0 | 426 | 0.2535 | 0.6225 | 0.4004 | 0.4873 | 0.9485 |
| 0.177 | 3.0 | 639 | 0.2773 | 0.6594 | 0.3911 | 0.4910 | 0.9497 |
| 0.177 | 4.0 | 852 | 0.2651 | 0.6098 | 0.4708 | 0.5314 | 0.9526 |
| 0.0551 | 5.0 | 1065 | 0.3076 | 0.6026 | 0.4652 | 0.5251 | 0.9514 |
| 0.0551 | 6.0 | 1278 | 0.3031 | 0.6343 | 0.4662 | 0.5374 | 0.9531 |
| 0.0551 | 7.0 | 1491 | 0.3319 | 0.6336 | 0.4680 | 0.5384 | 0.9523 |
| 0.0276 | 8.0 | 1704 | 0.3430 | 0.6508 | 0.4560 | 0.5362 | 0.9526 |
| 0.0276 | 9.0 | 1917 | 0.3342 | 0.6138 | 0.4773 | 0.5370 | 0.9521 |
| 0.0157 | 10.0 | 2130 | 0.3376 | 0.6252 | 0.4791 | 0.5425 | 0.9523 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu117
- Datasets 2.9.0
- Tokenizers 0.13.2
- Task
- Token Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Mar 14, 2023
- Updated
- Mar 14, 2023