--- license: llama2 base_model: codellama/CodeLlama-7b-Instruct-hf tags: - generated_from_trainer datasets: - tmnam20/SpiderInstruct model-index: - name: codellama_instruct_spider_e10 results: [] --- # codellama_instruct_spider_e10 This model is a fine-tuned version of [codellama/CodeLlama-7b-Instruct-hf](https://huggingface.co/codellama/CodeLlama-7b-Instruct-hf) on the tmnam20/SpiderInstruct dataset. It achieves the following results on the evaluation set: - Loss: 0.2393 ## 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: 5e-05 - train_batch_size: 4 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 8 - total_train_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.06 - num_epochs: 10.0 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 0.822 | 0.37 | 100 | 0.5313 | | 0.3014 | 0.74 | 200 | 0.2763 | | 0.2091 | 1.11 | 300 | 0.2469 | | 0.1697 | 1.48 | 400 | 0.2401 | | 0.1495 | 1.85 | 500 | 0.2395 | | 0.1256 | 2.22 | 600 | 0.2525 | | 0.1097 | 2.59 | 700 | 0.2641 | | 0.1107 | 2.96 | 800 | 0.2617 | | 0.0951 | 3.33 | 900 | 0.2683 | | 0.0882 | 3.7 | 1000 | 0.2892 | | 0.0818 | 4.06 | 1100 | 0.3134 | | 0.075 | 4.43 | 1200 | 0.2978 | | 0.0745 | 4.8 | 1300 | 0.3095 | | 0.0642 | 5.17 | 1400 | 0.3261 | | 0.0622 | 5.54 | 1500 | 0.3201 | | 0.0573 | 5.91 | 1600 | 0.3343 | | 0.0552 | 6.28 | 1700 | 0.3396 | | 0.0523 | 6.65 | 1800 | 0.3602 | | 0.0538 | 7.02 | 1900 | 0.3464 | | 0.0467 | 7.39 | 2000 | 0.3622 | | 0.0465 | 7.76 | 2100 | 0.3697 | | 0.044 | 8.13 | 2200 | 0.3890 | | 0.043 | 8.5 | 2300 | 0.3785 | | 0.0375 | 8.87 | 2400 | 0.3860 | | 0.0384 | 9.24 | 2500 | 0.3952 | | 0.0363 | 9.61 | 2600 | 0.3940 | | 0.0352 | 9.98 | 2700 | 0.3985 | ### Framework versions - Transformers 4.34.0.dev0 - Pytorch 2.0.1+cu118 - Datasets 2.14.4 - Tokenizers 0.13.3