--- base_model: vinai/bertweet-base tags: - generated_from_trainer metrics: - accuracy - f1 - precision - recall model-index: - name: bertweet-base_3epoch3.1 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. --> # bertweet-base_3epoch3.1 This model is a fine-tuned version of [vinai/bertweet-base](https://huggingface.co/vinai/bertweet-base) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.8308 - Accuracy: 0.7378 - F1: 0.4313 - Precision: 0.5702 - Recall: 0.3467 - Precision Sarcastic: 0.5702 - Recall Sarcastic: 0.3467 - F1 Sarcastic: 0.4313 ## 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: 32 - eval_batch_size: 32 - 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 | Accuracy | F1 | Precision | Recall | Precision Sarcastic | Recall Sarcastic | F1 Sarcastic | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-------------------:|:----------------:|:------------:| | No log | 1.0 | 87 | 1.5536 | 0.7493 | 0.3958 | 0.6404 | 0.2864 | 0.6404 | 0.2864 | 0.3958 | | No log | 2.0 | 174 | 1.7665 | 0.7392 | 0.4784 | 0.5608 | 0.4171 | 0.5608 | 0.4171 | 0.4784 | | No log | 3.0 | 261 | 1.8308 | 0.7378 | 0.4313 | 0.5702 | 0.3467 | 0.5702 | 0.3467 | 0.4313 | ### Framework versions - Transformers 4.41.2 - Pytorch 2.3.0+cu121 - Datasets 2.19.1 - Tokenizers 0.19.1