roberta_large-filtered_simple-chunk-conll2003_0907_v1
This model is a fine-tuned version of roberta-large on the conll2003 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1299
- Precision: 0.9048
- Recall: 0.8909
- F1: 0.8978
- Accuracy: 0.9657
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: 1e-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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.2061 | 1.0 | 878 | 0.1237 | 0.9077 | 0.9008 | 0.9042 | 0.9661 |
| 0.0999 | 2.0 | 1756 | 0.1131 | 0.9148 | 0.9079 | 0.9113 | 0.9687 |
Framework versions
- Transformers 4.21.3
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1