--- base_model: meta-llama/Llama-2-7b-hf tags: - generated_from_trainer model-index: - name: sparse_llama_7b_hf2_refined_web_70p_2024-03-28 results: [] --- # sparse_llama_7b_hf2_refined_web_70p_2024-03-28 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: 2.1370 ## 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: 4 - seed: 0 - distributed_type: multi-GPU - num_devices: 4 - gradient_accumulation_steps: 4 - total_train_batch_size: 16 - total_eval_batch_size: 16 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - training_steps: 2600 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 2.5973 | 0.0 | 25 | 2.4361 | | 2.3245 | 0.01 | 50 | 2.4253 | | 2.3668 | 0.01 | 75 | 2.4063 | | 2.3521 | 0.02 | 100 | 2.3820 | | 2.3119 | 0.02 | 125 | 2.3613 | | 2.4636 | 0.02 | 150 | 2.3452 | | 2.3372 | 0.03 | 175 | 2.3331 | | 2.2927 | 0.03 | 200 | 2.3267 | | 2.3831 | 0.04 | 225 | 2.3196 | | 2.4013 | 0.04 | 250 | 2.3158 | | 2.2576 | 0.04 | 275 | 2.3109 | | 2.2803 | 0.05 | 300 | 2.3104 | | 2.3531 | 0.05 | 325 | 2.3070 | | 2.0961 | 0.06 | 350 | 2.3066 | | 2.2809 | 0.06 | 375 | 2.3042 | | 2.4516 | 0.06 | 400 | 2.3034 | | 2.3927 | 0.07 | 425 | 2.3027 | | 2.3188 | 0.07 | 450 | 2.3030 | | 2.2165 | 0.08 | 475 | 2.3028 | | 2.2814 | 0.08 | 500 | 2.3003 | | 2.3224 | 0.08 | 525 | 2.3005 | | 2.2267 | 0.09 | 550 | 2.2991 | | 2.3238 | 0.09 | 575 | 2.2976 | | 2.1845 | 0.1 | 600 | 2.2992 | | 2.2896 | 0.1 | 625 | 2.2994 | | 2.334 | 0.1 | 650 | 2.2973 | | 2.3298 | 0.11 | 675 | 2.2972 | | 2.2847 | 0.11 | 700 | 2.2950 | | 2.2589 | 0.12 | 725 | 2.2966 | | 2.1715 | 0.12 | 750 | 2.2949 | | 2.3554 | 0.12 | 775 | 2.2940 | | 2.3217 | 0.13 | 800 | 2.2970 | | 2.3374 | 0.13 | 825 | 2.2940 | | 2.2951 | 0.14 | 850 | 2.2933 | | 2.1613 | 0.14 | 875 | 2.2934 | | 2.278 | 0.14 | 900 | 2.2928 | | 2.1964 | 0.15 | 925 | 2.2930 | | 2.3489 | 0.15 | 950 | 2.2926 | | 2.3561 | 0.16 | 975 | 2.2919 | | 2.3854 | 0.16 | 1000 | 2.2907 | | 2.3849 | 0.16 | 1025 | 2.2931 | | 2.2953 | 0.17 | 1050 | 2.2917 | | 2.3519 | 0.17 | 1075 | 2.2901 | | 2.2702 | 0.18 | 1100 | 2.2927 | | 2.2834 | 0.18 | 1125 | 2.2888 | | 2.4015 | 0.18 | 1150 | 2.2925 | | 2.3967 | 0.19 | 1175 | 2.2915 | | 2.1978 | 0.19 | 1200 | 2.2892 | | 2.2758 | 0.2 | 1225 | 2.2886 | | 2.2774 | 0.2 | 1250 | 2.2905 | | 2.3803 | 0.2 | 1275 | 2.2930 | | 2.3233 | 0.21 | 1300 | 2.2909 | | 2.2431 | 0.21 | 1325 | 2.2908 | | 2.2042 | 0.22 | 1350 | 2.2885 | | 2.3585 | 0.22 | 1375 | 2.2885 | | 2.2779 | 0.22 | 1400 | 2.2906 | | 2.2119 | 0.23 | 1425 | 2.2883 | | 2.2257 | 0.23 | 1450 | 2.2876 | | 2.2383 | 0.24 | 1475 | 2.2892 | | 2.2166 | 0.24 | 1500 | 2.2899 | | 2.1817 | 0.24 | 1525 | 2.2872 | | 2.3113 | 0.25 | 1550 | 2.2880 | | 2.3212 | 0.25 | 1575 | 2.2876 | | 2.3027 | 0.26 | 1600 | 2.2838 | | 2.2737 | 0.26 | 1625 | 2.2888 | | 2.3181 | 0.26 | 1650 | 2.2865 | | 2.2759 | 0.27 | 1675 | 2.2871 | | 2.3179 | 0.27 | 1700 | 2.2858 | | 2.3111 | 0.28 | 1725 | 2.2862 | | 2.2699 | 0.28 | 1750 | 2.2872 | | 2.3006 | 0.28 | 1775 | 2.2859 | | 2.1913 | 0.29 | 1800 | 2.2849 | | 2.3133 | 0.29 | 1825 | 2.2852 | | 2.286 | 0.3 | 1850 | 2.2849 | | 2.3403 | 0.3 | 1875 | 2.2860 | | 2.2713 | 0.3 | 1900 | 2.2843 | | 2.3492 | 0.31 | 1925 | 2.2840 | | 2.2747 | 0.31 | 1950 | 2.2840 | | 2.2783 | 0.32 | 1975 | 2.2841 | | 2.1854 | 0.32 | 2000 | 2.2836 | | 2.2544 | 0.32 | 2025 | 2.2826 | | 2.2955 | 0.33 | 2050 | 2.2837 | | 2.2053 | 0.33 | 2075 | 2.2849 | | 2.2848 | 0.34 | 2100 | 2.2841 | | 2.4168 | 0.34 | 2125 | 2.2843 | | 2.268 | 0.34 | 2150 | 2.2814 | | 2.2045 | 0.35 | 2175 | 2.2841 | | 2.2717 | 0.35 | 2200 | 2.2825 | | 2.1958 | 0.36 | 2225 | 2.2827 | | 2.1635 | 0.36 | 2250 | 2.2867 | | 2.3043 | 0.36 | 2275 | 2.2820 | | 2.3106 | 0.37 | 2300 | 2.2845 | | 2.1992 | 0.37 | 2325 | 2.2829 | | 2.2189 | 0.38 | 2350 | 2.2817 | | 2.3096 | 0.38 | 2375 | 2.2830 | | 2.2803 | 0.38 | 2400 | 2.2839 | | 2.1752 | 0.39 | 2425 | 2.2825 | | 2.1324 | 0.39 | 2450 | 2.2834 | | 2.207 | 0.4 | 2475 | 2.2846 | | 2.3369 | 0.4 | 2500 | 2.2844 | | 2.3512 | 0.4 | 2525 | 2.2853 | | 2.1432 | 0.41 | 2550 | 2.2861 | | 2.1743 | 0.41 | 2575 | 2.2832 | | 2.2696 | 0.42 | 2600 | 2.2832 | ### Framework versions - Transformers 4.40.0.dev0 - Pytorch 2.1.1+cu121 - Datasets 2.15.0 - Tokenizers 0.15.2