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deberta-v3-large-ad-opentag-finetuned-ner-2epochs
This model is a fine-tuned version of microsoft/deberta-v3-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0023
- Precision: 0.9843
- Recall: 0.9911
- F1: 0.9877
- Accuracy: 0.9996
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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0041 | 1.0 | 8909 | 0.0036 | 0.9746 | 0.9838 | 0.9792 | 0.9993 |
| 0.0032 | 2.0 | 17818 | 0.0023 | 0.9843 | 0.9911 | 0.9877 | 0.9996 |
Framework versions
- Transformers 4.30.1
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3
