xlm-roberta-large-finetuned-conll03-english
This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6008
- Precision: 0.4263
- Recall: 0.1404
- F1: 0.2112
- Accuracy: 0.9559
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 |
|---|
| 0.0001 | 1.0 | 29460 | 0.6008 | 0.4263 | 0.1404 | 0.2112 | 0.9559 |
| 0.0 | 2.0 | 58920 | 0.6008 | 0.4263 | 0.1404 | 0.2112 | 0.9559 |
| 0.0001 | 3.0 | 88380 | 0.6008 | 0.4263 | 0.1404 | 0.2112 | 0.9559 |
Framework versions
- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.1
