--- library_name: peft tags: - parquet - text-classification datasets: - tweet_eval metrics: - accuracy base_model: classla/bcms-bertic-parlasent-bcs-ter model-index: - name: classla_bcms-bertic-parlasent-bcs-ter-finetuned-lora-tweet_eval_irony results: - task: type: text-classification name: Text Classification dataset: name: tweet_eval type: tweet_eval config: irony split: validation args: irony metrics: - type: accuracy value: 0.6198952879581152 name: accuracy --- # classla_bcms-bertic-parlasent-bcs-ter-finetuned-lora-tweet_eval_irony This model is a fine-tuned version of [classla/bcms-bertic-parlasent-bcs-ter](https://huggingface.co/classla/bcms-bertic-parlasent-bcs-ter) on the tweet_eval dataset. It achieves the following results on the evaluation set: - accuracy: 0.6199 ## 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: 0.0005 - 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: 8 ### Training results | accuracy | train_loss | epoch | |:--------:|:----------:|:-----:| | 0.4681 | None | 0 | | 0.5822 | 0.7160 | 0 | | 0.5990 | 0.6825 | 1 | | 0.6073 | 0.6548 | 2 | | 0.6052 | 0.6302 | 3 | | 0.6188 | 0.6116 | 4 | | 0.5969 | 0.6127 | 5 | | 0.6230 | 0.6000 | 6 | | 0.6199 | 0.5972 | 7 | ### Framework versions - PEFT 0.8.2 - Transformers 4.37.2 - Pytorch 2.2.0 - Datasets 2.16.1 - Tokenizers 0.15.2