distilbert-base-uncased-finetuned-ner
This model is a fine-tuned version of distilbert-base-uncased on the maccrobat_biomedical_ner dataset. It achieves the following results on the evaluation set:
- Loss: 2.4960
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.4185
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: 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: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 10 | 2.9692 | 0.0 | 0.0 | 0.0 | 0.4185 |
No log | 2.0 | 20 | 2.5900 | 0.0 | 0.0 | 0.0 | 0.4185 |
No log | 3.0 | 30 | 2.4960 | 0.0 | 0.0 | 0.0 | 0.4185 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for NeverLearn/distilbert-base-uncased-finetuned-ner
Base model
distilbert/distilbert-base-uncasedEvaluation results
- Precision on maccrobat_biomedical_nerself-reported0.000
- Recall on maccrobat_biomedical_nerself-reported0.000
- F1 on maccrobat_biomedical_nerself-reported0.000
- Accuracy on maccrobat_biomedical_nerself-reported0.418