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roberta-base-NER-favsbot
This model is a fine-tuned version of roberta-base on the favsbot dataset. It achieves the following results on the evaluation set:
- Loss: 0.4812
- Precision: 0.6940
- Recall: 0.7056
- F1: 0.6997
- Accuracy: 0.8454
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: 1.5e-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: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 4 | 2.1885 | 0.1787 | 0.3722 | 0.2414 | 0.2998 |
| No log | 2.0 | 8 | 1.9109 | 0.3768 | 0.1444 | 0.2088 | 0.4707 |
| No log | 3.0 | 12 | 1.6425 | 0.0 | 0.0 | 0.0 | 0.4075 |
| No log | 4.0 | 16 | 1.5402 | 0.75 | 0.0167 | 0.0326 | 0.4145 |
| No log | 5.0 | 20 | 1.3569 | 0.5263 | 0.3333 | 0.4082 | 0.5785 |
| No log | 6.0 | 24 | 1.2250 | 0.4691 | 0.5056 | 0.4866 | 0.6721 |
| No log | 7.0 | 28 | 1.0957 | 0.4973 | 0.5167 | 0.5068 | 0.6885 |
| No log | 8.0 | 32 | 0.9751 | 0.5581 | 0.5333 | 0.5455 | 0.7190 |
| No log | 9.0 | 36 | 0.8824 | 0.6456 | 0.5667 | 0.6036 | 0.7518 |
| No log | 10.0 | 40 | 0.8035 | 0.6442 | 0.5833 | 0.6122 | 0.7658 |
| No log | 11.0 | 44 | 0.7336 | 0.6412 | 0.6056 | 0.6229 | 0.7822 |
| No log | 12.0 | 48 | 0.6722 | 0.6384 | 0.6278 | 0.6331 | 0.7963 |
| No log | 13.0 | 52 | 0.6205 | 0.6610 | 0.65 | 0.6555 | 0.8080 |
| No log | 14.0 | 56 | 0.5796 | 0.6740 | 0.6778 | 0.6759 | 0.8244 |
| No log | 15.0 | 60 | 0.5503 | 0.6796 | 0.6833 | 0.6814 | 0.8244 |
| No log | 16.0 | 64 | 0.5256 | 0.6851 | 0.6889 | 0.6870 | 0.8337 |
| No log | 17.0 | 68 | 0.5066 | 0.6868 | 0.6944 | 0.6906 | 0.8407 |
| No log | 18.0 | 72 | 0.4929 | 0.6868 | 0.6944 | 0.6906 | 0.8431 |
| No log | 19.0 | 76 | 0.4845 | 0.6868 | 0.6944 | 0.6906 | 0.8431 |
| No log | 20.0 | 80 | 0.4812 | 0.6940 | 0.7056 | 0.6997 | 0.8454 |
Framework versions
- Transformers 4.21.1
- Pytorch 1.12.1
- Datasets 2.4.0
- Tokenizers 0.12.1
