metadata
license: mit
base_model: microsoft/deberta-v3-small
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: DeBERTaV3_model_multilabel
results: []
DeBERTaV3_model_multilabel
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: 0.3255
- Accuracy: 0.8667
- F1: 0.7333
- Precision: 0.8148
- Recall: 0.6667
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 | 25 | 0.4956 | 0.7667 | 0.4167 | 0.6667 | 0.3030 |
| No log | 2.0 | 50 | 0.4877 | 0.7667 | 0.4167 | 0.6667 | 0.3030 |
| No log | 3.0 | 75 | 0.4476 | 0.7667 | 0.4167 | 0.6667 | 0.3030 |
| No log | 4.0 | 100 | 0.4332 | 0.7833 | 0.4800 | 0.7059 | 0.3636 |
| No log | 5.0 | 125 | 0.3847 | 0.8167 | 0.6071 | 0.7391 | 0.5152 |
| No log | 6.0 | 150 | 0.3680 | 0.8583 | 0.7302 | 0.7667 | 0.6970 |
| No log | 7.0 | 175 | 0.3332 | 0.8667 | 0.7500 | 0.7742 | 0.7273 |
| No log | 8.0 | 200 | 0.3545 | 0.85 | 0.7000 | 0.7778 | 0.6364 |
| No log | 9.0 | 225 | 0.3255 | 0.8667 | 0.7333 | 0.8148 | 0.6667 |
| No log | 10.0 | 250 | 0.3322 | 0.8583 | 0.7213 | 0.7857 | 0.6667 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1