| | --- |
| | library_name: transformers |
| | license: mit |
| | base_model: microsoft/deberta-v3-large |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: microsoft-deberta-v3-large |
| | 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. --> |
| |
|
| | # microsoft-deberta-v3-large |
| |
|
| | This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.5698 |
| | - Pearson R: 0.8241 |
| | - Spearman R: 0.8276 |
| |
|
| | ## 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: 0.0005 |
| | - train_batch_size: 8 |
| | - eval_batch_size: 64 |
| | - seed: 42 |
| | - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| | - lr_scheduler_type: cosine |
| | - lr_scheduler_warmup_ratio: 0.1 |
| | - num_epochs: 10 |
| | - mixed_precision_training: Native AMP |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Pearson R | Spearman R | |
| | |:-------------:|:-----:|:----:|:---------------:|:---------:|:----------:| |
| | | 0.6835 | 1.0 | 719 | 0.6543 | 0.5224 | 0.5221 | |
| | | 0.6489 | 2.0 | 1438 | 0.6053 | 0.7743 | 0.7848 | |
| | | 0.6408 | 3.0 | 2157 | 0.6005 | 0.7826 | 0.7938 | |
| | | 0.6288 | 4.0 | 2876 | 0.5970 | 0.7778 | 0.7792 | |
| | | 0.6138 | 5.0 | 3595 | 0.6643 | 0.7622 | 0.7814 | |
| | | 0.6044 | 6.0 | 4314 | 0.6048 | 0.8059 | 0.8135 | |
| | | 0.597 | 7.0 | 5033 | 0.5865 | 0.8243 | 0.8307 | |
| | | 0.5946 | 8.0 | 5752 | 0.5702 | 0.8170 | 0.8236 | |
| | | 0.5915 | 9.0 | 6471 | 0.5738 | 0.8211 | 0.8242 | |
| | | 0.5891 | 10.0 | 7190 | 0.5698 | 0.8241 | 0.8276 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.49.0 |
| | - Pytorch 2.6.0+cu124 |
| | - Datasets 3.3.2 |
| | - Tokenizers 0.21.0 |
| | |
