|  | --- | 
					
						
						|  | license: bigcode-openrail-m | 
					
						
						|  | library_name: peft | 
					
						
						|  | tags: | 
					
						
						|  | - generated_from_trainer | 
					
						
						|  | base_model: bigcode/starcoder2-15b | 
					
						
						|  | datasets: | 
					
						
						|  | - andstor/methods2test_small | 
					
						
						|  | metrics: | 
					
						
						|  | - accuracy | 
					
						
						|  | model-index: | 
					
						
						|  | - name: output | 
					
						
						|  | results: | 
					
						
						|  | - task: | 
					
						
						|  | type: text-generation | 
					
						
						|  | name: Causal Language Modeling | 
					
						
						|  | dataset: | 
					
						
						|  | name: andstor/methods2test_small fm+fc+c+m+f+t+tc | 
					
						
						|  | type: andstor/methods2test_small | 
					
						
						|  | args: fm+fc+c+m+f+t+tc | 
					
						
						|  | metrics: | 
					
						
						|  | - type: accuracy | 
					
						
						|  | value: 0.8050969652164623 | 
					
						
						|  | name: Accuracy | 
					
						
						|  | --- | 
					
						
						|  |  | 
					
						
						|  | <!-- This model card has been generated automatically according to the information the Trainer had access to. You | 
					
						
						|  | should probably proofread and complete it, then remove this comment. --> | 
					
						
						|  |  | 
					
						
						|  | [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/andstor/methods2test_small/runs/83rqm3hd) | 
					
						
						|  | # output | 
					
						
						|  |  | 
					
						
						|  | This model is a fine-tuned version of [bigcode/starcoder2-15b](https://huggingface.co/bigcode/starcoder2-15b) on the andstor/methods2test_small fm+fc+c+m+f+t+tc dataset. | 
					
						
						|  | It achieves the following results on the evaluation set: | 
					
						
						|  | - Loss: 0.6419 | 
					
						
						|  | - Accuracy: 0.8051 | 
					
						
						|  |  | 
					
						
						|  | ## 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: 0.0003 | 
					
						
						|  | - train_batch_size: 1 | 
					
						
						|  | - eval_batch_size: 1 | 
					
						
						|  | - seed: 42 | 
					
						
						|  | - gradient_accumulation_steps: 8 | 
					
						
						|  | - total_train_batch_size: 8 | 
					
						
						|  | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | 
					
						
						|  | - lr_scheduler_type: linear | 
					
						
						|  | - lr_scheduler_warmup_ratio: 0.1 | 
					
						
						|  | - num_epochs: 3.0 | 
					
						
						|  |  | 
					
						
						|  | ### Training results | 
					
						
						|  |  | 
					
						
						|  |  | 
					
						
						|  |  | 
					
						
						|  | ### Framework versions | 
					
						
						|  |  | 
					
						
						|  | - PEFT 0.11.1 | 
					
						
						|  | - Transformers 4.42.0.dev0 | 
					
						
						|  | - Pytorch 2.2.1+cu118 | 
					
						
						|  | - Datasets 2.17.1 | 
					
						
						|  | - Tokenizers 0.19.1 |