--- license: llama2 library_name: peft tags: - generated_from_trainer base_model: codellama/CodeLlama-7b-Instruct-hf model-index: - name: finetuningnewmodule4 results: [] --- # finetuningnewmodule4 This model is a fine-tuned version of [codellama/CodeLlama-7b-Instruct-hf](https://huggingface.co/codellama/CodeLlama-7b-Instruct-hf) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.9178 ## 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: 0.001 - 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: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 2.688 | 1.0 | 1 | 2.7462 | | 2.261 | 2.0 | 2 | 2.2006 | | 1.7646 | 3.0 | 3 | 1.9486 | | 1.518 | 4.0 | 4 | 1.7189 | | 1.2896 | 5.0 | 5 | 1.4255 | | 0.9851 | 6.0 | 6 | 1.1951 | | 0.7157 | 7.0 | 7 | 1.0503 | | 0.496 | 8.0 | 8 | 0.9871 | | 0.3614 | 9.0 | 9 | 0.9348 | | 0.2587 | 10.0 | 10 | 0.9178 | ### Framework versions - Transformers 4.36.0 - Pytorch 2.0.1 - Datasets 2.16.1 - Tokenizers 0.15.1 ## Training procedure ### Framework versions - PEFT 0.6.0