bert-finetuned-ner
This model is a fine-tuned version of FacebookAI/roberta-large on the few-nerd dataset. It achieves the following results on the evaluation set:
- Loss: 0.2164
- Precision: 0.7845
- Recall: 0.8148
- F1: 0.7993
- Accuracy: 0.9429
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: 4
- eval_batch_size: 4
- 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 |
|---|---|---|---|---|---|---|---|
| 0.1953 | 1.0 | 32942 | 0.1933 | 0.7670 | 0.7968 | 0.7816 | 0.9395 |
| 0.1573 | 2.0 | 65884 | 0.2051 | 0.7850 | 0.8034 | 0.7941 | 0.9416 |
| 0.1256 | 3.0 | 98826 | 0.2164 | 0.7845 | 0.8148 | 0.7993 | 0.9429 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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Base model
FacebookAI/roberta-largeEvaluation results
- Precision on few-nerdvalidation set self-reported0.784
- Recall on few-nerdvalidation set self-reported0.815
- F1 on few-nerdvalidation set self-reported0.799
- Accuracy on few-nerdvalidation set self-reported0.943