--- license: apache-2.0 library_name: peft tags: - parquet - text-classification datasets: - glue metrics: - accuracy base_model: marcelcastrobr/sagemaker-distilbert-emotion model-index: - name: marcelcastrobr_sagemaker-distilbert-emotion-finetuned-lora-glue_cola results: - task: type: text-classification name: Text Classification dataset: name: glue type: glue config: cola split: validation args: cola metrics: - type: accuracy value: 0.7535953978907 name: accuracy --- # marcelcastrobr_sagemaker-distilbert-emotion-finetuned-lora-glue_cola This model is a fine-tuned version of [marcelcastrobr/sagemaker-distilbert-emotion](https://huggingface.co/marcelcastrobr/sagemaker-distilbert-emotion) on the glue dataset. It achieves the following results on the evaluation set: - accuracy: 0.7536 ## 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 | |:--------:|:----------:|:-----:| | 0.6702 | None | 0 | | 0.7095 | 0.6043 | 0 | | 0.7354 | 0.5365 | 1 | | 0.7555 | 0.5047 | 2 | | 0.7536 | 0.4836 | 3 | ### Framework versions - PEFT 0.8.2 - Transformers 4.37.2 - Pytorch 2.2.0 - Datasets 2.16.1 - Tokenizers 0.15.2