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distilbert-base-uncased-finetuned-ner
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.2393
- Precision: 1.0
- Recall: 1.0
- F1: 1.0
- Accuracy: 1.0
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 | 1 | 1.5491 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 2.0 | 2 | 1.3278 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 3.0 | 3 | 1.2393 | 1.0 | 1.0 | 1.0 | 1.0 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2
