| | --- |
| | license: mit |
| | base_model: microsoft/deberta-v3-base |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - f1 |
| | - precision |
| | - recall |
| | model-index: |
| | - name: deberta-v3-base-orgs-v2 |
| | 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. --> |
| |
|
| | # deberta-v3-base-orgs-v2 |
| |
|
| | This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Accuracy: 0.9632 |
| | - F1: 0.7927 |
| | - Loss: 0.1186 |
| | - Precision: 0.8127 |
| | - Recall: 0.7735 |
| |
|
| | ## 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: 0.0003 |
| | - train_batch_size: 256 |
| | - eval_batch_size: 256 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_steps: 20 |
| | - num_epochs: 3.0 |
| | - mixed_precision_training: Native AMP |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Accuracy | F1 | Validation Loss | Precision | Recall | |
| | |:-------------:|:-----:|:----:|:--------:|:------:|:---------------:|:---------:|:------:| |
| | | 0.0706 | 0.7 | 600 | 0.9602 | 0.7690 | 0.1138 | 0.7590 | 0.7793 | |
| | | 0.0526 | 1.4 | 1200 | 0.9617 | 0.7870 | 0.1113 | 0.7942 | 0.7799 | |
| | | 0.0409 | 2.11 | 1800 | 0.9627 | 0.7875 | 0.1125 | 0.7911 | 0.7839 | |
| | | 0.0376 | 2.81 | 2400 | 0.9632 | 0.7927 | 0.1186 | 0.8127 | 0.7735 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.35.2 |
| | - Pytorch 2.1.0a0+32f93b1 |
| | - Datasets 2.15.0 |
| | - Tokenizers 0.15.0 |
| | |
