ajrayman/AuthorityRespect_continuous

1---2library_name: transformers3license: mit4base_model: microsoft/deberta-v3-base5tags:6- generated_from_trainer7model-index:8- name: AuthorityRespect_continuous9  results: []10---11 12<!-- This model card has been generated automatically according to the information the Trainer had access to. You13should probably proofread and complete it, then remove this comment. -->14 15# AuthorityRespect_continuous16 17This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.18It achieves the following results on the evaluation set:19- Loss: 0.034420- Rmse: 0.185421- Mae: 0.145222- Corr: 0.276523 24## Model description25 26More information needed27 28## Intended uses & limitations29 30More information needed31 32## Training and evaluation data33 34More information needed35 36## Training procedure37 38### Training hyperparameters39 40The following hyperparameters were used during training:41- learning_rate: 2e-0542- train_batch_size: 3243- eval_batch_size: 3244- seed: 123445- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-0846- lr_scheduler_type: linear47- lr_scheduler_warmup_ratio: 0.0648- num_epochs: 849 50### Training results51 52| Training Loss | Epoch | Step | Validation Loss | Rmse   | Mae    | Corr   |53|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|54| No log        | 1.0   | 220  | 0.0333          | 0.1825 | 0.1418 | 0.2839 |55| No log        | 2.0   | 440  | 0.0311          | 0.1765 | 0.1385 | 0.2980 |56| 0.049         | 3.0   | 660  | 0.0357          | 0.1890 | 0.1463 | 0.2800 |57| 0.049         | 4.0   | 880  | 0.0344          | 0.1854 | 0.1452 | 0.2765 |58 59 60### Framework versions61 62- Transformers 4.44.163- Pytorch 1.11.064- Datasets 2.12.065- Tokenizers 0.19.166