--- license: other library_name: peft tags: - generated_from_trainer datasets: - glue metrics: - accuracy base_model: facebook/opt-350m model-index: - name: opt-350m-pattern-based_finetuning_with_lora-mnli-mm-d3_fs1 results: [] --- # opt-350m-pattern-based_finetuning_with_lora-mnli-mm-d3_fs1 This model is a fine-tuned version of [facebook/opt-350m](https://huggingface.co/facebook/opt-350m) on the glue dataset. It achieves the following results on the evaluation set: - Loss: 1.6609 - Accuracy: 0.5313 ## 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: 2e-06 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 1.0844 | 1.0 | 1 | 1.6609 | 0.5313 | | 1.0899 | 2.0 | 2 | 1.6647 | 0.5311 | | 1.045 | 3.0 | 3 | 1.6674 | 0.5308 | | 1.0959 | 4.0 | 4 | 1.6694 | 0.5308 | | 0.8649 | 5.0 | 5 | 1.6703 | 0.5308 | ### Framework versions - PEFT 0.7.1.dev0 - Transformers 4.36.0.dev0 - Pytorch 2.1.0+cu118 - Datasets 2.15.0 - Tokenizers 0.15.0