| license: mit | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - accuracy | |
| - f1 | |
| - precision | |
| - recall | |
| model-index: | |
| - name: outputs | |
| 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. --> | |
| # outputs | |
| This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on the None dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.0926 | |
| - Accuracy: 0.8780 | |
| - F1: 0.3881 | |
| - Precision: 0.5417 | |
| - Recall: 0.3023 | |
| ## 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: 8e-05 | |
| - train_batch_size: 256 | |
| - eval_batch_size: 512 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: cosine | |
| - lr_scheduler_warmup_ratio: 0.1 | |
| - num_epochs: 4 | |
| - mixed_precision_training: Native AMP | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| | |
| | No log | 1.0 | 6 | 0.0874 | 0.8810 | 0.4118 | 0.56 | 0.3256 | | |
| | No log | 2.0 | 12 | 0.0936 | 0.8839 | 0.4000 | 0.5909 | 0.3023 | | |
| | No log | 3.0 | 18 | 0.0922 | 0.8780 | 0.3881 | 0.5417 | 0.3023 | | |
| | No log | 4.0 | 24 | 0.0926 | 0.8780 | 0.3881 | 0.5417 | 0.3023 | | |
| ### Framework versions | |
| - Transformers 4.20.1 | |
| - Pytorch 1.11.0 | |
| - Datasets 2.1.0 | |
| - Tokenizers 0.12.1 | |