distilbert-NER-finetuned-bert-tiny
This model is a fine-tuned version of dslim/distilbert-NER on the conll2012_ontonotesv5 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5602
- F1: 0.4683
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: 5e-05
- train_batch_size: 24
- eval_batch_size: 24
- 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 | F1 |
|---|---|---|---|---|
| 1.0495 | 1.0 | 81 | 0.7833 | 0.3529 |
| 0.6421 | 2.0 | 162 | 0.6088 | 0.4570 |
| 0.5065 | 3.0 | 243 | 0.5602 | 0.4683 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
- Downloads last month
- 9
Model tree for chineidu/distilbert-NER-finetuned-bert-tiny
Dataset used to train chineidu/distilbert-NER-finetuned-bert-tiny
Evaluation results
- F1 on conll2012_ontonotesv5validation set self-reported0.468