deberta-v3-large-orgs-v1
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: 0.1343
- Precision: 0.8037
- Recall: 0.7601
- F1: 0.7813
- Accuracy: 0.9617
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 20
- num_epochs: 3.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0612 | 1.0 | 1710 | 0.1069 | 0.7827 | 0.7741 | 0.7784 | 0.9612 |
| 0.0502 | 2.0 | 3420 | 0.1225 | 0.8034 | 0.7461 | 0.7737 | 0.9606 |
| 0.0285 | 3.0 | 5130 | 0.1343 | 0.8037 | 0.7601 | 0.7813 | 0.9617 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0a0+32f93b1
- Datasets 2.15.0
- Tokenizers 0.15.0