--- license: apache-2.0 library_name: peft tags: - parquet - text-classification datasets: - tweet_eval metrics: - accuracy base_model: dapang/distilroberta-base-mic-sym model-index: - name: dapang_distilroberta-base-mic-sym-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: 0.6952879581151833 name: accuracy --- # dapang_distilroberta-base-mic-sym-finetuned-lora-tweet_eval_irony This model is a fine-tuned version of [dapang/distilroberta-base-mic-sym](https://huggingface.co/dapang/distilroberta-base-mic-sym) on the tweet_eval dataset. It achieves the following results on the evaluation set: - accuracy: 0.6953 ## 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 | |:--------:|:----------:|:-----:| | 0.4785 | None | 0 | | 0.6084 | 0.7298 | 0 | | 0.6178 | 0.6248 | 1 | | 0.6670 | 0.5899 | 2 | | 0.6859 | 0.5613 | 3 | | 0.7005 | 0.5578 | 4 | | 0.6576 | 0.5267 | 5 | | 0.6974 | 0.5210 | 6 | | 0.6953 | 0.5141 | 7 | ### Framework versions - PEFT 0.8.2 - Transformers 4.37.2 - Pytorch 2.2.0 - Datasets 2.16.1 - Tokenizers 0.15.2