Downloads · 30 days
24
3% of all-time downloads
CNEC1_1_xlm-roberta-large
stulcrad/CNEC1_1_xlm-roberta-large
CNEC1_1_xlm-roberta-large is a token classification model from stulcrad. 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
729
Public
Parameters
559M
257 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.pt4.5 GB · 50%
At a glance
- Task
- Token Classification
- Library
- transformers
- License
- mit
- Model type
- xlm-roberta
- Access
- Public
- Created
- Mar 3, 2024
- Updated
- May 9, 2024
- SHA
- a6b6fb42
Try a prompt
Base models
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. -->
CNEC1_1_xlm-roberta-large
This model is a fine-tuned version of FacebookAI/xlm-roberta-large on the cnec dataset. It achieves the following results on the evaluation set:
- Loss: 0.3816
- Precision: 0.8521
- Recall: 0.8721
- F1: 0.8620
- Accuracy: 0.9513
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.4004 | 1.0 | 1174 | 0.2747 | 0.7598 | 0.7876 | 0.7735 | 0.9381 |
| 0.2765 | 2.0 | 2348 | 0.2268 | 0.8181 | 0.8340 | 0.8260 | 0.9506 |
| 0.2104 | 3.0 | 3522 | 0.2400 | 0.8318 | 0.8561 | 0.8438 | 0.9524 |
| 0.1713 | 4.0 | 4696 | 0.2285 | 0.8353 | 0.8645 | 0.8496 | 0.9552 |
| 0.1241 | 5.0 | 5870 | 0.2278 | 0.8458 | 0.8715 | 0.8584 | 0.9585 |
| 0.0997 | 6.0 | 7044 | 0.2717 | 0.8372 | 0.8653 | 0.8511 | 0.9559 |
| 0.0878 | 7.0 | 8218 | 0.2599 | 0.8439 | 0.8830 | 0.8630 | 0.9583 |
| 0.0585 | 8.0 | 9392 | 0.2868 | 0.8415 | 0.8764 | 0.8586 | 0.9564 |
| 0.0489 | 9.0 | 10566 | 0.2900 | 0.8594 | 0.8795 | 0.8693 | 0.9568 |
| 0.0416 | 10.0 | 11740 | 0.3061 | 0.8646 | 0.8852 | 0.8748 | 0.9598 |
| 0.0316 | 11.0 | 12914 | 0.3240 | 0.8567 | 0.8843 | 0.8703 | 0.9576 |
| 0.0264 | 12.0 | 14088 | 0.3329 | 0.8546 | 0.8795 | 0.8668 | 0.9588 |
| 0.0184 | 13.0 | 15262 | 0.3475 | 0.8628 | 0.8804 | 0.8715 | 0.9584 |
| 0.0156 | 14.0 | 16436 | 0.3472 | 0.8654 | 0.8826 | 0.8739 | 0.9592 |
| 0.0125 | 15.0 | 17610 | 0.3539 | 0.8670 | 0.8861 | 0.8764 | 0.9593 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
- Task
- Token Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Mar 3, 2024
- Updated
- May 9, 2024