metadata
license: mit
base_model: microsoft/deberta-v3-small
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: DeBERTaV3_model_V2
results: []
DeBERTaV3_model_V2
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: 0.1711
- Accuracy: 0.9412
- F1: 0.7500
- Precision: 0.8
- Recall: 0.7059
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: 5e-05
- train_batch_size: 5
- eval_batch_size: 5
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 50 | 0.3627 | 0.875 | 0.0 | 0.0 | 0.0 |
| No log | 2.0 | 100 | 0.3804 | 0.875 | 0.0 | 0.0 | 0.0 |
| No log | 3.0 | 150 | 0.3085 | 0.8934 | 0.2564 | 1.0 | 0.1471 |
| No log | 4.0 | 200 | 0.2722 | 0.9007 | 0.4706 | 0.7059 | 0.3529 |
| No log | 5.0 | 250 | 0.2206 | 0.9118 | 0.6129 | 0.6786 | 0.5588 |
| No log | 6.0 | 300 | 0.2140 | 0.9265 | 0.6667 | 0.7692 | 0.5882 |
| No log | 7.0 | 350 | 0.2022 | 0.9265 | 0.6875 | 0.7333 | 0.6471 |
| No log | 8.0 | 400 | 0.1940 | 0.9301 | 0.7077 | 0.7419 | 0.6765 |
| No log | 9.0 | 450 | 0.1711 | 0.9412 | 0.7500 | 0.8 | 0.7059 |
| 0.2198 | 10.0 | 500 | 0.1778 | 0.9338 | 0.7188 | 0.7667 | 0.6765 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1