| | --- |
| | license: mit |
| | base_model: microsoft/deberta-v3-small |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - f1 |
| | - precision |
| | - recall |
| | model-index: |
| | - name: results |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # results |
| |
|
| | This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on the KMC dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0556 |
| | - Accuracy: 0.8722 |
| | - F1: 0.8849 |
| | - Precision: 0.8950 |
| | - Recall: 0.8750 |
| |
|
| | ## 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: 8 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 5 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
| | | 0.0894 | 1.0 | 1633 | 0.0817 | 0.7508 | 0.8072 | 0.8774 | 0.7474 | |
| | | 0.059 | 2.0 | 3266 | 0.0620 | 0.8264 | 0.8520 | 0.8815 | 0.8243 | |
| | | 0.0429 | 3.0 | 4899 | 0.0531 | 0.8563 | 0.8751 | 0.8947 | 0.8563 | |
| | | 0.032 | 4.0 | 6532 | 0.0547 | 0.8704 | 0.8838 | 0.8976 | 0.8705 | |
| | | 0.0253 | 5.0 | 8165 | 0.0556 | 0.8722 | 0.8849 | 0.8950 | 0.8750 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.41.2 |
| | - Pytorch 2.3.0+cu121 |
| | - Datasets 2.20.0 |
| | - Tokenizers 0.19.1 |
| |
|
