metadata
license: mit
base_model: microsoft/deberta-v3-small
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: DeBERTaV3_model
results: []
DeBERTaV3_model
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: 0.1419
- Accuracy: 0.9615
- F1: 0.8400
- Precision: 0.875
- Recall: 0.8077
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 | 26 | 0.3810 | 0.875 | 0.0 | 0.0 | 0.0 |
| No log | 2.0 | 52 | 0.3740 | 0.875 | 0.0 | 0.0 | 0.0 |
| No log | 3.0 | 78 | 0.3303 | 0.875 | 0.0 | 0.0 | 0.0 |
| No log | 4.0 | 104 | 0.2997 | 0.875 | 0.0 | 0.0 | 0.0 |
| No log | 5.0 | 130 | 0.2484 | 0.8894 | 0.2581 | 0.8 | 0.1538 |
| No log | 6.0 | 156 | 0.1951 | 0.9375 | 0.6977 | 0.8824 | 0.5769 |
| No log | 7.0 | 182 | 0.1752 | 0.9423 | 0.7273 | 0.8889 | 0.6154 |
| No log | 8.0 | 208 | 0.1582 | 0.9519 | 0.7917 | 0.8636 | 0.7308 |
| No log | 9.0 | 234 | 0.1449 | 0.9615 | 0.8400 | 0.875 | 0.8077 |
| No log | 10.0 | 260 | 0.1419 | 0.9615 | 0.8400 | 0.875 | 0.8077 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1