|  | --- | 
					
						
						|  | license: llama2 | 
					
						
						|  | base_model: meta-llama/CodeLlama-34b-Instruct-hf | 
					
						
						|  | tags: | 
					
						
						|  | - alignment-handbook | 
					
						
						|  | - generated_from_trainer | 
					
						
						|  | datasets: | 
					
						
						|  | - meng-lab/CodeLlama-34B-Instruct-gsm8k | 
					
						
						|  | model-index: | 
					
						
						|  | - name: CodeLlama-34b-Instruct-sft-5e-3-epoch-100-gsm8k | 
					
						
						|  | results: [] | 
					
						
						|  | --- | 
					
						
						|  |  | 
					
						
						|  | <!-- 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/uva-llm/huggingface/runs/nemwhwry) | 
					
						
						|  | # CodeLlama-34b-Instruct-sft-5e-3-epoch-100-gsm8k | 
					
						
						|  |  | 
					
						
						|  | This model is a fine-tuned version of [meta-llama/CodeLlama-34b-Instruct-hf](https://huggingface.co/meta-llama/CodeLlama-34b-Instruct-hf) on the meng-lab/CodeLlama-34B-Instruct-gsm8k dataset. | 
					
						
						|  | It achieves the following results on the evaluation set: | 
					
						
						|  | - Loss: 4.0230 | 
					
						
						|  | - Loss Layer 6 Head: 1.2898 | 
					
						
						|  | - Loss Layer 12 Head: 1.0049 | 
					
						
						|  | - Loss Layer 18 Head: 0.9093 | 
					
						
						|  | - Loss Layer 24 Head: 0.4408 | 
					
						
						|  | - Loss Layer 30 Head: 0.2683 | 
					
						
						|  | - Loss Layer 36 Head: 0.1391 | 
					
						
						|  | - Loss Layer 42 Head: 0.0639 | 
					
						
						|  |  | 
					
						
						|  | ## 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: 0.005 | 
					
						
						|  | - train_batch_size: 1 | 
					
						
						|  | - eval_batch_size: 2 | 
					
						
						|  | - seed: 42 | 
					
						
						|  | - distributed_type: multi-GPU | 
					
						
						|  | - num_devices: 8 | 
					
						
						|  | - gradient_accumulation_steps: 16 | 
					
						
						|  | - total_train_batch_size: 128 | 
					
						
						|  | - total_eval_batch_size: 16 | 
					
						
						|  | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | 
					
						
						|  | - lr_scheduler_type: cosine | 
					
						
						|  | - lr_scheduler_warmup_ratio: 0.1 | 
					
						
						|  | - num_epochs: 100 | 
					
						
						|  |  | 
					
						
						|  | ### Training results | 
					
						
						|  |  | 
					
						
						|  | | Training Loss | Epoch   | Step | Validation Loss | Loss Layer 6 Head | Loss Layer 12 Head | Loss Layer 18 Head | Loss Layer 24 Head | Loss Layer 30 Head | Loss Layer 36 Head | Loss Layer 42 Head | | 
					
						
						|  | |:-------------:|:-------:|:----:|:---------------:|:-----------------:|:------------------:|:------------------:|:------------------:|:------------------:|:------------------:|:------------------:| | 
					
						
						|  | | 2.6241        | 25.8065 | 200  | 4.3768          | 1.3707            | 1.0927             | 0.9492             | 0.4907             | 0.2888             | 0.1534             | 0.0899             | | 
					
						
						|  | | 1.6189        | 51.6129 | 400  | 4.0476          | 1.3067            | 0.9916             | 0.9104             | 0.4445             | 0.2716             | 0.1405             | 0.0663             | | 
					
						
						|  | | 1.3737        | 77.4194 | 600  | 4.0230          | 1.2898            | 1.0049             | 0.9093             | 0.4408             | 0.2683             | 0.1391             | 0.0639             | | 
					
						
						|  |  | 
					
						
						|  |  | 
					
						
						|  | ### Framework versions | 
					
						
						|  |  | 
					
						
						|  | - Transformers 4.43.2 | 
					
						
						|  | - Pytorch 2.1.2 | 
					
						
						|  | - Datasets 3.2.0 | 
					
						
						|  | - Tokenizers 0.19.1 | 
					
						
						|  |  |