| license: apache-2.0 | |
| tags: | |
| - generated_from_trainer | |
| datasets: | |
| - tweet_eval | |
| metrics: | |
| - precision | |
| - recall | |
| model-index: | |
| - name: bert-emotion | |
| results: | |
| - task: | |
| name: Text Classification | |
| type: text-classification | |
| dataset: | |
| name: tweet_eval | |
| type: tweet_eval | |
| config: emotion | |
| split: validation | |
| args: emotion | |
| metrics: | |
| - name: Precision | |
| type: precision | |
| value: 0.7505623807659564 | |
| - name: Recall | |
| type: recall | |
| value: 0.7243031825553111 | |
| <!-- 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. --> | |
| # bert-emotion | |
| This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the tweet_eval dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 1.1413 | |
| - Precision: 0.7506 | |
| - Recall: 0.7243 | |
| - Fscore: 0.7340 | |
| ## 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: 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 | Fscore | | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:| | |
| | 0.8556 | 1.0 | 815 | 0.7854 | 0.7461 | 0.5929 | 0.6088 | | |
| | 0.5369 | 2.0 | 1630 | 0.9014 | 0.7549 | 0.7278 | 0.7359 | | |
| | 0.2571 | 3.0 | 2445 | 1.1413 | 0.7506 | 0.7243 | 0.7340 | | |
| ### Framework versions | |
| - Transformers 4.29.2 | |
| - Pytorch 2.0.1+cu118 | |
| - Datasets 2.12.0 | |
| - Tokenizers 0.13.3 | |