--- base_model: meta-llama/Llama-2-7b-hf tags: - generated_from_trainer model-index: - name: llama_7b_hf_relu_refined_web_relu_2024-03-27 results: [] --- # llama_7b_hf_relu_refined_web_relu_2024-03-27 This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.8945 ## 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: 1e-05 - train_batch_size: 1 - eval_batch_size: 1 - seed: 0 - distributed_type: multi-GPU - num_devices: 4 - gradient_accumulation_steps: 8 - total_train_batch_size: 32 - total_eval_batch_size: 4 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - training_steps: 400 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 9.5817 | 0.01 | 25 | 9.2314 | | 7.8754 | 0.02 | 50 | 7.6756 | | 6.6513 | 0.02 | 75 | 6.5579 | | 5.5276 | 0.03 | 100 | 5.4724 | | 4.8802 | 0.04 | 125 | 4.7672 | | 4.1435 | 0.05 | 150 | 4.2747 | | 3.7831 | 0.06 | 175 | 3.9269 | | 3.6802 | 0.06 | 200 | 3.6937 | | 3.5049 | 0.07 | 225 | 3.5292 | | 3.3127 | 0.08 | 250 | 3.4086 | | 3.1939 | 0.09 | 275 | 3.3188 | | 3.149 | 0.1 | 300 | 3.2472 | | 3.0679 | 0.1 | 325 | 3.1902 | | 3.0111 | 0.11 | 350 | 3.1422 | | 2.9573 | 0.12 | 375 | 3.1011 | | 3.0001 | 0.13 | 400 | 3.0645 | ### Framework versions - Transformers 4.40.0.dev0 - Pytorch 2.1.1+cu121 - Datasets 2.15.0 - Tokenizers 0.15.2