--- library_name: peft tags: - parquet - text-classification datasets: - tweet_eval metrics: - accuracy base_model: Splend1dchan/bert-base-uncased-slue-goldtrascription-e3-lr1e-4 model-index: - name: Splend1dchan_bert-base-uncased-slue-goldtrascription-e3-lr1e-4-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 --- # Splend1dchan_bert-base-uncased-slue-goldtrascription-e3-lr1e-4-finetuned-lora-tweet_eval_irony This model is a fine-tuned version of [Splend1dchan/bert-base-uncased-slue-goldtrascription-e3-lr1e-4](https://huggingface.co/Splend1dchan/bert-base-uncased-slue-goldtrascription-e3-lr1e-4) 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 | |:--------:|:----------:|:-----:| | 0.5152 | None | 0 | | 0.6230 | 0.6797 | 0 | | 0.6251 | 0.6591 | 1 | | 0.6419 | 0.6296 | 2 | | 0.6618 | 0.5978 | 3 | | 0.6817 | 0.5772 | 4 | | 0.6743 | 0.5497 | 5 | | 0.6827 | 0.5394 | 6 | | 0.6869 | 0.5343 | 7 | ### Framework versions - PEFT 0.8.2 - Transformers 4.37.2 - Pytorch 2.2.0 - Datasets 2.16.1 - Tokenizers 0.15.2