metadata
license: mit
base_model: microsoft/deberta-v3-small
tags:
- generated_from_trainer
metrics:
- recall
- precision
model-index:
- name: deberta-v3-small-finetuned-ner-2048
results: []
deberta-v3-small-finetuned-ner-2048
This model is a fine-tuned version of microsoft/deberta-v3-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0036
- Recall: 0.9920
- Precision: 0.9866
- Fbeta Score: 0.9918
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Recall | Precision | Fbeta Score |
|---|---|---|---|---|---|---|
| 0.0085 | 1.0 | 3186 | 0.0058 | 0.9786 | 0.9693 | 0.9782 |
| 0.0032 | 2.0 | 6373 | 0.0036 | 0.9869 | 0.9764 | 0.9865 |
| 0.004 | 3.0 | 9559 | 0.0037 | 0.9791 | 0.9892 | 0.9795 |
| 0.0014 | 4.0 | 12746 | 0.0035 | 0.9908 | 0.9817 | 0.9905 |
| 0.0019 | 5.0 | 15932 | 0.0038 | 0.9903 | 0.9806 | 0.9899 |
| 0.0022 | 6.0 | 19119 | 0.0032 | 0.9929 | 0.9861 | 0.9927 |
| 0.0005 | 7.0 | 22305 | 0.0031 | 0.9906 | 0.9894 | 0.9905 |
| 0.0003 | 8.0 | 25492 | 0.0033 | 0.9915 | 0.9855 | 0.9913 |
| 0.0001 | 9.0 | 28678 | 0.0036 | 0.9920 | 0.9866 | 0.9918 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2