HeRo-finetuned-ner
This model is a fine-tuned version of HeNLP/HeRo on the nemo_corpus dataset. It achieves the following results on the evaluation set:
- Loss: 0.1244
- Precision: 0.8626
- Recall: 0.8485
- F1: 0.8555
- Accuracy: 0.9769
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 |
---|---|---|---|---|---|---|---|
0.2734 | 1.0 | 618 | 0.1445 | 0.8125 | 0.7576 | 0.7841 | 0.9667 |
0.0939 | 2.0 | 1236 | 0.1258 | 0.8449 | 0.8380 | 0.8414 | 0.9748 |
0.0545 | 3.0 | 1854 | 0.1244 | 0.8626 | 0.8485 | 0.8555 | 0.9769 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.0.1+cpu
- Datasets 2.15.0
- Tokenizers 0.15.0
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Base model
HeNLP/HeRoEvaluation results
- Precision on nemo_corpusvalidation set self-reported0.863
- Recall on nemo_corpusvalidation set self-reported0.848
- F1 on nemo_corpusvalidation set self-reported0.855
- Accuracy on nemo_corpusvalidation set self-reported0.977