--- base_model: meta-llama/Llama-2-13b-hf tags: - generated_from_trainer metrics: - accuracy model-index: - name: Llama-2-13b-lr-5e-5 results: [] --- # Llama-2-13b-lr-5e-5 This model is a fine-tuned version of [meta-llama/Llama-2-13b-hf](https://huggingface.co/meta-llama/Llama-2-13b-hf) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.1454 - Accuracy: 0.2150 ## 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: 2 - eval_batch_size: 2 - seed: 42 - distributed_type: multi-GPU - num_devices: 16 - total_train_batch_size: 32 - total_eval_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.03 - num_epochs: 3.0 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.955 | 0.37 | 10 | 0.9061 | 0.2182 | | 0.8899 | 0.74 | 20 | 0.8734 | 0.2196 | | 0.879 | 1.11 | 30 | 0.9091 | 0.2174 | | 0.3295 | 1.48 | 40 | 0.9803 | 0.2173 | | 0.3711 | 1.85 | 50 | 0.9820 | 0.2174 | | 0.2927 | 2.22 | 60 | 1.0270 | 0.2153 | | 0.1703 | 2.59 | 70 | 1.0966 | 0.2131 | | 0.2011 | 2.96 | 80 | 1.1488 | 0.2145 | ### Framework versions - Transformers 4.35.2 - Pytorch 2.1.0+cu121 - Datasets 2.15.0 - Tokenizers 0.15.0