| license: apache-2.0 | |
| tags: | |
| - generated_from_trainer | |
| datasets: | |
| - emotion | |
| metrics: | |
| - accuracy | |
| model-index: | |
| - name: twitter_emotions | |
| results: | |
| - task: | |
| name: Text Classification | |
| type: text-classification | |
| dataset: | |
| name: emotion | |
| type: emotion | |
| args: default | |
| metrics: | |
| - name: Accuracy | |
| type: accuracy | |
| value: 0.9375 | |
| <!-- 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. --> | |
| # twitter_emotions | |
| This model is a fine-tuned version of [sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2](https://huggingface.co/sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2) on the emotion dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.1647 | |
| - Accuracy: 0.9375 | |
| ## 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: 5e-05 | |
| - train_batch_size: 8 | |
| - eval_batch_size: 8 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 3.0 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| | |
| | 0.2486 | 1.0 | 2000 | 0.2115 | 0.931 | | |
| | 0.135 | 2.0 | 4000 | 0.1725 | 0.936 | | |
| | 0.1041 | 3.0 | 6000 | 0.1647 | 0.9375 | | |
| ### Framework versions | |
| - Transformers 4.12.5 | |
| - Pytorch 1.10.0+cu111 | |
| - Datasets 1.15.1 | |
| - Tokenizers 0.10.3 | |