xlm-roberta-base-uk-base-ner
This model is a fine-tuned version of xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2510
- Precision: 0.5951
- Recall: 0.6256
- F1: 0.6100
- Accuracy: 0.9264
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: 32
- eval_batch_size: 32
- 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 |
---|---|---|---|---|---|---|---|
0.7224 | 1.0 | 514 | 0.3856 | 0.4590 | 0.4581 | 0.4586 | 0.8996 |
0.3616 | 2.0 | 1028 | 0.2893 | 0.5528 | 0.5533 | 0.5531 | 0.9190 |
0.2783 | 3.0 | 1542 | 0.2652 | 0.5661 | 0.5965 | 0.5809 | 0.9227 |
0.2362 | 4.0 | 2056 | 0.2531 | 0.5882 | 0.6256 | 0.6063 | 0.9263 |
0.2124 | 5.0 | 2570 | 0.2510 | 0.5951 | 0.6256 | 0.6100 | 0.9264 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
- Downloads last month
- 6
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.