metadata
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: deberta-v3-base-DIALOCONAN-WIKI-CLS
results: []
deberta-v3-base-DIALOCONAN-WIKI-CLS
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: 0.3828
- Precision: 0.7060
- Recall: 0.7086
- F1: 0.7072
- Accuracy: 0.9422
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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.4295 | 1.0 | 2500 | 0.5694 | 0.6816 | 0.6816 | 0.6793 | 0.9040 |
| 0.3525 | 2.0 | 5000 | 0.4852 | 0.6923 | 0.6938 | 0.6928 | 0.9225 |
| 0.2604 | 3.0 | 7500 | 0.4372 | 0.6993 | 0.7005 | 0.6995 | 0.9314 |
| 0.1979 | 4.0 | 10000 | 0.4076 | 0.7056 | 0.7077 | 0.7065 | 0.9410 |
| 0.1295 | 5.0 | 12500 | 0.3828 | 0.7060 | 0.7086 | 0.7072 | 0.9422 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1