| license: mit | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - precision | |
| - recall | |
| - f1 | |
| model-index: | |
| - name: deberta-base-TEST | |
| 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-base-TEST | |
| This model is a fine-tuned version of [microsoft/deberta-base](https://huggingface.co/microsoft/deberta-base) on an unknown dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.3385 | |
| - Precision: 0.9472 | |
| - Recall: 0.9472 | |
| - F1: 0.9472 | |
| ## 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: 3e-05 | |
| - train_batch_size: 4 | |
| - eval_batch_size: 4 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 3 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:| | |
| | 0.3683 | 1.0 | 2500 | 0.3859 | 0.9094 | 0.9094 | 0.9094 | | |
| | 0.2269 | 2.0 | 5000 | 0.3091 | 0.9439 | 0.9439 | 0.9439 | | |
| | 0.1006 | 3.0 | 7500 | 0.3385 | 0.9472 | 0.9472 | 0.9472 | | |
| ### Framework versions | |
| - Transformers 4.30.2 | |
| - Pytorch 2.0.1+cu118 | |
| - Datasets 2.13.1 | |
| - Tokenizers 0.13.3 | |