| | --- |
| | license: mit |
| | base_model: microsoft/deberta-v3-large |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: Classifier_with_external_sets_04 |
| | 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. --> |
| |
|
| | # Classifier_with_external_sets_04 |
| |
|
| | This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.2741 |
| | - Accuracy: 0.9193 |
| |
|
| | ## 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 |
| | - gradient_accumulation_steps: 4 |
| | - total_train_batch_size: 32 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 26 |
| | - mixed_precision_training: Native AMP |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-------:|:----:|:---------------:|:--------:| |
| | | No log | 0.9983 | 289 | 0.3540 | 0.8893 | |
| | | 0.5256 | 2.0 | 579 | 0.3874 | 0.8673 | |
| | | 0.5256 | 2.9983 | 868 | 0.3275 | 0.8991 | |
| | | 0.378 | 4.0 | 1158 | 0.3244 | 0.9028 | |
| | | 0.378 | 4.9983 | 1447 | 0.4013 | 0.8312 | |
| | | 0.4029 | 6.0 | 1737 | 0.4052 | 0.8428 | |
| | | 0.3932 | 6.9983 | 2026 | 0.3667 | 0.8801 | |
| | | 0.3932 | 8.0 | 2316 | 0.3972 | 0.8385 | |
| | | 0.3972 | 8.9983 | 2605 | 0.3983 | 0.8648 | |
| | | 0.3972 | 10.0 | 2895 | 0.3805 | 0.8587 | |
| | | 0.3734 | 10.9983 | 3184 | 0.3735 | 0.8746 | |
| | | 0.3734 | 12.0 | 3474 | 0.3256 | 0.8893 | |
| | | 0.3752 | 12.9983 | 3763 | 0.2800 | 0.9101 | |
| | | 0.3169 | 14.0 | 4053 | 0.3071 | 0.8979 | |
| | | 0.3169 | 14.9983 | 4342 | 0.3083 | 0.9052 | |
| | | 0.312 | 16.0 | 4632 | 0.2894 | 0.9168 | |
| | | 0.312 | 16.9983 | 4921 | 0.3725 | 0.8624 | |
| | | 0.3162 | 18.0 | 5211 | 0.3163 | 0.8979 | |
| | | 0.3185 | 18.9983 | 5500 | 0.3030 | 0.8991 | |
| | | 0.3185 | 20.0 | 5790 | 0.3045 | 0.8997 | |
| | | 0.2951 | 20.9983 | 6079 | 0.2944 | 0.9076 | |
| | | 0.2951 | 22.0 | 6369 | 0.2693 | 0.9199 | |
| | | 0.2916 | 22.9983 | 6658 | 0.2711 | 0.9187 | |
| | | 0.2916 | 24.0 | 6948 | 0.2651 | 0.9211 | |
| | | 0.2593 | 24.9983 | 7237 | 0.2696 | 0.9193 | |
| | | 0.2646 | 25.9551 | 7514 | 0.2741 | 0.9193 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.40.0 |
| | - Pytorch 2.2.2+cu121 |
| | - Datasets 2.19.0 |
| | - Tokenizers 0.19.1 |
| | |
