deberta-v3-base-company-names
This model is a fine-tuned version of microsoft/deberta-v3-base on the nbroad/company_names dataset. It achieves the following results on the evaluation set:
- Loss: 0.0693
- Precision: 0.7740
- Recall: 0.7963
- F1: 0.7850
- Accuracy: 0.9769
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: 8e-05
- train_batch_size: 48
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0752 | 1.0 | 2126 | 0.0664 | 0.7416 | 0.7979 | 0.7687 | 0.9757 |
| 0.0484 | 2.0 | 4252 | 0.0652 | 0.7725 | 0.7903 | 0.7813 | 0.9768 |
| 0.0415 | 3.0 | 6378 | 0.0693 | 0.7740 | 0.7963 | 0.7850 | 0.9769 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.0.1+cu117
- Datasets 2.16.1
- Tokenizers 0.14.1