metadata
license: mit
base_model: microsoft/deberta-v3-small
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: DeBERTaV3_model_V3
results: []
DeBERTaV3_model_V3
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: 0.0963
- Accuracy: 0.9724
- F1: 0.8874
- Precision: 0.9054
- Recall: 0.8701
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 | 84 | 0.2797 | 0.9058 | 0.4630 | 0.8065 | 0.3247 |
| No log | 2.0 | 168 | 0.2004 | 0.9269 | 0.6281 | 0.8636 | 0.4935 |
| No log | 3.0 | 252 | 0.1818 | 0.9253 | 0.6761 | 0.7385 | 0.6234 |
| No log | 4.0 | 336 | 0.1692 | 0.9399 | 0.7176 | 0.8704 | 0.6104 |
| No log | 5.0 | 420 | 0.1503 | 0.9513 | 0.7945 | 0.8406 | 0.7532 |
| 0.2044 | 6.0 | 504 | 0.1269 | 0.9562 | 0.8212 | 0.8378 | 0.8052 |
| 0.2044 | 7.0 | 588 | 0.0963 | 0.9724 | 0.8874 | 0.9054 | 0.8701 |
| 0.2044 | 8.0 | 672 | 0.1243 | 0.9594 | 0.8344 | 0.8514 | 0.8182 |
| 0.2044 | 9.0 | 756 | 0.1107 | 0.9659 | 0.8609 | 0.8784 | 0.8442 |
| 0.2044 | 10.0 | 840 | 0.1088 | 0.9675 | 0.8667 | 0.8904 | 0.8442 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1