--- library_name: peft tags: - parquet - text-classification datasets: - tweet_eval metrics: - accuracy base_model: Jeevesh8/feather_berts_46 model-index: - name: Jeevesh8_feather_berts_46-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: 0.6869109947643979 name: accuracy --- # Jeevesh8_feather_berts_46-finetuned-lora-tweet_eval_irony This model is a fine-tuned version of [Jeevesh8/feather_berts_46](https://huggingface.co/Jeevesh8/feather_berts_46) on the tweet_eval dataset. It achieves the following results on the evaluation set: - accuracy: 0.6869 ## 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 | |:--------:|:----------:|:-----:| | 0.5225 | None | 0 | | 0.6220 | 0.6878 | 0 | | 0.6607 | 0.6468 | 1 | | 0.6555 | 0.5991 | 2 | | 0.6639 | 0.5766 | 3 | | 0.6670 | 0.5570 | 4 | | 0.6702 | 0.5481 | 5 | | 0.6775 | 0.5330 | 6 | | 0.6869 | 0.5180 | 7 | ### Framework versions - PEFT 0.8.2 - Transformers 4.37.2 - Pytorch 2.2.0 - Datasets 2.16.1 - Tokenizers 0.15.2