roberta-large-aces
This model is a fine-tuned version of roberta-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5257
- Precision: 0.8561
- Recall: 0.8594
- F1: 0.8553
- Accuracy: 0.8594
- F1 Who: 0.8494
- F1 What: 0.8391
- F1 Where: 0.7558
- F1 How: 0.9208
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | F1 Who | F1 What | F1 Where | F1 How |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.4619 | 1.0 | 87 | 0.5447 | 0.8247 | 0.8416 | 0.8308 | 0.8416 | 0.8309 | 0.8188 | 0.6973 | 0.9244 |
| 0.4358 | 2.0 | 174 | 0.4662 | 0.8522 | 0.8571 | 0.8517 | 0.8571 | 0.8314 | 0.8446 | 0.7613 | 0.9238 |
| 0.3793 | 3.0 | 261 | 0.4892 | 0.8507 | 0.8622 | 0.8556 | 0.8622 | 0.8321 | 0.8418 | 0.7725 | 0.9280 |
| 0.2875 | 4.0 | 348 | 0.5034 | 0.8702 | 0.8641 | 0.8593 | 0.8641 | 0.8471 | 0.8441 | 0.7715 | 0.9225 |
| 0.1847 | 5.0 | 435 | 0.5257 | 0.8561 | 0.8594 | 0.8553 | 0.8594 | 0.8494 | 0.8391 | 0.7558 | 0.9208 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.13.2