metadata
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: cyner_deberta
results: []
cyner_deberta
This model is a fine-tuned version of microsoft/deberta-v3-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0685
- Precision: 0.7801
- Recall: 0.8110
- F1: 0.7952
- Accuracy: 0.9839
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: 10.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1285 | 1.42 | 500 | 0.0762 | 0.7305 | 0.8033 | 0.7652 | 0.9823 |
| 0.041 | 2.84 | 1000 | 0.0685 | 0.7801 | 0.8110 | 0.7952 | 0.9839 |
| 0.024 | 4.26 | 1500 | 0.0796 | 0.7957 | 0.8008 | 0.7982 | 0.9855 |
| 0.0156 | 5.68 | 2000 | 0.0747 | 0.7836 | 0.8276 | 0.8050 | 0.9858 |
| 0.0106 | 7.1 | 2500 | 0.0817 | 0.7961 | 0.8327 | 0.8140 | 0.9859 |
| 0.0064 | 8.52 | 3000 | 0.0828 | 0.7942 | 0.8429 | 0.8178 | 0.9865 |
| 0.0049 | 9.94 | 3500 | 0.0858 | 0.7976 | 0.8352 | 0.8160 | 0.9865 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1