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: 0.0221
- Accuracy: 0.9919
- F1: 0.3922
- Precision: 0.6667
- Recall: 0.2778
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 | 0.4442 | 0.9516 | 0.1475 | 0.0884 | 0.4444 |
| No log | 2.0 | 50 | 0.1757 | 0.9919 | 0.3922 | 0.6667 | 0.2778 |
| No log | 3.0 | 75 | 0.0655 | 0.9919 | 0.3922 | 0.6667 | 0.2778 |
| No log | 4.0 | 100 | 0.0378 | 0.9919 | 0.3922 | 0.6667 | 0.2778 |
| No log | 5.0 | 125 | 0.0292 | 0.9919 | 0.3922 | 0.6667 | 0.2778 |
| No log | 6.0 | 150 | 0.0255 | 0.9919 | 0.3922 | 0.6667 | 0.2778 |
| No log | 7.0 | 175 | 0.0238 | 0.9919 | 0.3922 | 0.6667 | 0.2778 |
| No log | 8.0 | 200 | 0.0227 | 0.9919 | 0.3922 | 0.6667 | 0.2778 |
| No log | 9.0 | 225 | 0.0222 | 0.9919 | 0.3922 | 0.6667 | 0.2778 |
| No log | 10.0 | 250 | 0.0221 | 0.9919 | 0.3922 | 0.6667 | 0.2778 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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Base model
microsoft/deberta-v3-small