--- license: apache-2.0 library_name: peft tags: - parquet - text-classification datasets: - tweet_eval metrics: - accuracy base_model: aXhyra/presentation_emotion_31415 model-index: - name: aXhyra_presentation_emotion_31415-finetuned-lora-tweet_eval_hate results: - task: type: text-classification name: Text Classification dataset: name: tweet_eval type: tweet_eval config: hate split: validation args: hate metrics: - type: accuracy value: 0.738 name: accuracy --- # aXhyra_presentation_emotion_31415-finetuned-lora-tweet_eval_hate This model is a fine-tuned version of [aXhyra/presentation_emotion_31415](https://huggingface.co/aXhyra/presentation_emotion_31415) on the tweet_eval dataset. It achieves the following results on the evaluation set: - accuracy: 0.738 ## 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: 0.0004 - 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: 4 ### Training results | accuracy | train_loss | epoch | |:--------:|:----------:|:-----:| | 0.462 | None | 0 | | 0.715 | 0.5597 | 0 | | 0.732 | 0.4657 | 1 | | 0.725 | 0.4318 | 2 | | 0.738 | 0.4147 | 3 | ### Framework versions - PEFT 0.8.2 - Transformers 4.37.2 - Pytorch 2.2.0 - Datasets 2.16.1 - Tokenizers 0.15.2