fin_subcate
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: 0.0671
- Accuracy: 0.6825
- F1: 0.7671
- Precision: 0.8756
- Recall: 0.6825
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: 2e-05
- train_batch_size: 64
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 64 | 0.1875 | 0.0 | 0.0 | 0.0 | 0.0 |
| No log | 2.0 | 128 | 0.1179 | 0.5134 | 0.6578 | 0.9153 | 0.5134 |
| No log | 3.0 | 192 | 0.0931 | 0.5124 | 0.6680 | 0.9593 | 0.5124 |
| No log | 4.0 | 256 | 0.0798 | 0.6231 | 0.7343 | 0.8936 | 0.6231 |
| No log | 5.0 | 320 | 0.0717 | 0.6508 | 0.7550 | 0.8989 | 0.6508 |
| No log | 6.0 | 384 | 0.0684 | 0.6746 | 0.7629 | 0.8777 | 0.6746 |
| No log | 7.0 | 448 | 0.0671 | 0.6825 | 0.7671 | 0.8756 | 0.6825 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Base model
microsoft/deberta-v3-small