| license: apache-2.0 | |
| tags: | |
| - generated_from_trainer | |
| datasets: | |
| - emotion | |
| metrics: | |
| - accuracy | |
| model-index: | |
| - name: twitter-emotion-deberta-v3-base | |
| results: | |
| - task: | |
| name: Text Classification | |
| type: text-classification | |
| dataset: | |
| name: emotion | |
| type: emotion | |
| args: default | |
| metrics: | |
| - name: Accuracy | |
| type: accuracy | |
| value: 0.937 | |
| - task: | |
| type: text-classification | |
| name: Text Classification | |
| dataset: | |
| name: emotion | |
| type: emotion | |
| config: default | |
| split: test | |
| metrics: | |
| - name: Accuracy | |
| type: accuracy | |
| value: 0.9255 | |
| verified: true | |
| - name: Precision Macro | |
| type: precision | |
| value: 0.8915483806374028 | |
| verified: true | |
| - name: Precision Micro | |
| type: precision | |
| value: 0.9255 | |
| verified: true | |
| - name: Precision Weighted | |
| type: precision | |
| value: 0.9286522707274408 | |
| verified: true | |
| - name: Recall Macro | |
| type: recall | |
| value: 0.875946770128528 | |
| verified: true | |
| - name: Recall Micro | |
| type: recall | |
| value: 0.9255 | |
| verified: true | |
| - name: Recall Weighted | |
| type: recall | |
| value: 0.9255 | |
| verified: true | |
| - name: F1 Macro | |
| type: f1 | |
| value: 0.8790048313120858 | |
| verified: true | |
| - name: F1 Micro | |
| type: f1 | |
| value: 0.9255 | |
| verified: true | |
| - name: F1 Weighted | |
| type: f1 | |
| value: 0.92449885920049 | |
| verified: true | |
| - name: loss | |
| type: loss | |
| value: 0.16804923117160797 | |
| verified: true | |
| # twitter-emotion-deberta-v3-base | |
| This model is a fine-tuned version of [DeBERTa-v3](https://huggingface.co/microsoft/deberta-v3-base). It achieves the following results on the evaluation set: | |
| - Loss: 0.1474 | |
| - Accuracy: 0.937 | |
| ### Training hyperparameters | |
| The following hyperparameters were used during training: | |
| - learning_rate: 5e-05 | |
| - train_batch_size: 80 | |
| - eval_batch_size: 80 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 6.0 | |
| ### Framework versions | |
| - Transformers 4.12.5 | |
| - Pytorch 1.10.0+cu113 | |
| - Datasets 1.15.1 | |
| - Tokenizers 0.10.3 |