--- license: mit base_model: openai-community/gpt2 tags: - generated_from_trainer datasets: - gokuls/wiki_book_corpus_raw_dataset_tiny metrics: - accuracy model-index: - name: gpt_train_12_512 results: - task: name: Causal Language Modeling type: text-generation dataset: name: gokuls/wiki_book_corpus_raw_dataset_tiny type: gokuls/wiki_book_corpus_raw_dataset_tiny metrics: - name: Accuracy type: accuracy value: 0.09167533902983765 --- # gpt_train_12_512 This model is a fine-tuned version of [openai-community/gpt2](https://huggingface.co/openai-community/gpt2) on the gokuls/wiki_book_corpus_raw_dataset_tiny dataset. It achieves the following results on the evaluation set: - Loss: 8.9141 - Accuracy: 0.0917 ## 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: 24 - eval_batch_size: 24 - seed: 10 - distributed_type: multi-GPU - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 100 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:------:|:----:|:---------------:|:--------:| | 10.8828 | 0.0000 | 1 | 10.8828 | 0.0001 | | 10.8984 | 0.0001 | 2 | 10.8828 | 0.0001 | | 10.8906 | 0.0001 | 3 | 10.8828 | 0.0001 | | 10.8828 | 0.0001 | 4 | 10.8828 | 0.0001 | | 10.8828 | 0.0002 | 5 | 10.8828 | 0.0001 | | 10.8828 | 0.0002 | 6 | 10.8828 | 0.0001 | | 10.8906 | 0.0003 | 7 | 10.8828 | 0.0001 | | 10.8828 | 0.0003 | 8 | 10.8828 | 0.0001 | | 10.875 | 0.0003 | 9 | 10.8828 | 0.0001 | | 10.8984 | 0.0004 | 10 | 10.8828 | 0.0001 | | 10.8828 | 0.0004 | 11 | 10.8828 | 0.0001 | | 10.8906 | 0.0004 | 12 | 10.8828 | 0.0001 | | 10.8828 | 0.0005 | 13 | 10.8828 | 0.0001 | | 10.8828 | 0.0005 | 14 | 10.8828 | 0.0001 | | 10.8828 | 0.0005 | 15 | 10.8828 | 0.0001 | | 10.8828 | 0.0006 | 16 | 10.8828 | 0.0001 | | 10.875 | 0.0006 | 17 | 10.8828 | 0.0001 | | 10.8828 | 0.0007 | 18 | 10.6328 | 0.0197 | | 10.6641 | 0.0007 | 19 | 10.4844 | 0.0444 | | 10.5078 | 0.0007 | 20 | 10.3828 | 0.0499 | | 10.3984 | 0.0008 | 21 | 10.3125 | 0.0532 | | 10.3438 | 0.0008 | 22 | 10.25 | 0.0550 | | 10.2656 | 0.0008 | 23 | 10.2031 | 0.0562 | | 10.25 | 0.0009 | 24 | 10.1641 | 0.0540 | | 10.1875 | 0.0009 | 25 | 10.1328 | 0.0470 | | 10.125 | 0.0009 | 26 | 10.1094 | 0.0461 | | 10.125 | 0.0010 | 27 | 10.0859 | 0.0480 | | 10.0938 | 0.0010 | 28 | 10.0703 | 0.0474 | | 10.0625 | 0.0011 | 29 | 10.0547 | 0.0465 | | 10.0703 | 0.0011 | 30 | 10.0391 | 0.0472 | | 10.0156 | 0.0011 | 31 | 10.0234 | 0.0515 | | 10.0859 | 0.0012 | 32 | 10.0156 | 0.0587 | | 9.9922 | 0.0012 | 33 | 10.0078 | 0.0613 | | 10.0234 | 0.0012 | 34 | 9.9922 | 0.0608 | | 9.9609 | 0.0013 | 35 | 9.9844 | 0.0600 | | 10.0391 | 0.0013 | 36 | 9.9766 | 0.0608 | | 9.9922 | 0.0013 | 37 | 9.9609 | 0.0619 | | 9.9688 | 0.0014 | 38 | 9.9531 | 0.0623 | | 9.9453 | 0.0014 | 39 | 9.9375 | 0.0622 | | 9.9609 | 0.0015 | 40 | 9.9297 | 0.0628 | | 9.9609 | 0.0015 | 41 | 9.9141 | 0.0640 | | 10.0234 | 0.0015 | 42 | 9.8984 | 0.0649 | | 9.9375 | 0.0016 | 43 | 9.8906 | 0.0648 | | 9.8516 | 0.0016 | 44 | 9.875 | 0.0644 | | 9.8672 | 0.0016 | 45 | 9.8594 | 0.0643 | | 9.8984 | 0.0017 | 46 | 9.8438 | 0.0643 | | 9.875 | 0.0017 | 47 | 9.8359 | 0.0645 | | 9.8672 | 0.0017 | 48 | 9.8203 | 0.0646 | | 9.8984 | 0.0018 | 49 | 9.8125 | 0.0649 | | 9.7891 | 0.0018 | 50 | 9.8047 | 0.0653 | | 9.8281 | 0.0019 | 51 | 9.7891 | 0.0655 | | 9.8281 | 0.0019 | 52 | 9.7812 | 0.0654 | | 9.7969 | 0.0019 | 53 | 9.7734 | 0.0660 | | 9.7812 | 0.0020 | 54 | 9.7656 | 0.0670 | | 9.8047 | 0.0020 | 55 | 9.75 | 0.0682 | | 9.7969 | 0.0020 | 56 | 9.7422 | 0.0688 | | 9.7891 | 0.0021 | 57 | 9.7344 | 0.0691 | | 9.6875 | 0.0021 | 58 | 9.7266 | 0.0690 | | 9.7188 | 0.0021 | 59 | 9.7188 | 0.0686 | | 9.7344 | 0.0022 | 60 | 9.7109 | 0.0682 | | 9.7344 | 0.0022 | 61 | 9.6953 | 0.0687 | | 9.7578 | 0.0023 | 62 | 9.6875 | 0.0697 | | 9.6484 | 0.0023 | 63 | 9.6719 | 0.0708 | | 9.6328 | 0.0023 | 64 | 9.6641 | 0.0715 | | 9.7656 | 0.0024 | 65 | 9.6562 | 0.0721 | | 9.6875 | 0.0024 | 66 | 9.6484 | 0.0725 | | 9.6328 | 0.0024 | 67 | 9.6406 | 0.0727 | | 9.6953 | 0.0025 | 68 | 9.6328 | 0.0734 | | 9.7188 | 0.0025 | 69 | 9.625 | 0.0744 | | 9.6875 | 0.0025 | 70 | 9.6172 | 0.0753 | | 9.625 | 0.0026 | 71 | 9.6094 | 0.0763 | | 9.6172 | 0.0026 | 72 | 9.6016 | 0.0769 | | 9.6016 | 0.0027 | 73 | 9.5938 | 0.0771 | | 9.6094 | 0.0027 | 74 | 9.5859 | 0.0771 | | 9.5859 | 0.0027 | 75 | 9.5781 | 0.0771 | | 9.5859 | 0.0028 | 76 | 9.5703 | 0.0767 | | 9.5859 | 0.0028 | 77 | 9.5625 | 0.0765 | | 9.5781 | 0.0028 | 78 | 9.5547 | 0.0764 | | 9.6172 | 0.0029 | 79 | 9.5469 | 0.0763 | | 9.5859 | 0.0029 | 80 | 9.5391 | 0.0768 | | 9.5859 | 0.0029 | 81 | 9.5312 | 0.0770 | | 9.5391 | 0.0030 | 82 | 9.5234 | 0.0770 | | 9.5391 | 0.0030 | 83 | 9.5234 | 0.0764 | | 9.5312 | 0.0031 | 84 | 9.5156 | 0.0758 | | 9.5547 | 0.0031 | 85 | 9.5078 | 0.0757 | | 9.5781 | 0.0031 | 86 | 9.5 | 0.0760 | | 9.5703 | 0.0032 | 87 | 9.4922 | 0.0764 | | 9.4844 | 0.0032 | 88 | 9.4844 | 0.0764 | | 9.5312 | 0.0032 | 89 | 9.4766 | 0.0765 | | 9.5312 | 0.0033 | 90 | 9.4688 | 0.0765 | | 9.5078 | 0.0033 | 91 | 9.4688 | 0.0766 | | 9.5 | 0.0033 | 92 | 9.4609 | 0.0768 | | 9.4844 | 0.0034 | 93 | 9.4531 | 0.0769 | | 9.4688 | 0.0034 | 94 | 9.4453 | 0.0773 | | 9.5156 | 0.0035 | 95 | 9.4375 | 0.0777 | | 9.4453 | 0.0035 | 96 | 9.4297 | 0.0783 | | 9.4766 | 0.0035 | 97 | 9.4219 | 0.0794 | | 9.4219 | 0.0036 | 98 | 9.4219 | 0.0804 | | 9.4531 | 0.0036 | 99 | 9.4141 | 0.0814 | | 9.4141 | 0.0036 | 100 | 9.4062 | 0.0819 | | 9.375 | 0.0037 | 101 | 9.3984 | 0.0825 | | 9.4219 | 0.0037 | 102 | 9.3906 | 0.0828 | | 9.3828 | 0.0037 | 103 | 9.3828 | 0.0828 | | 9.375 | 0.0038 | 104 | 9.3828 | 0.0827 | | 9.3516 | 0.0038 | 105 | 9.375 | 0.0825 | | 9.3906 | 0.0039 | 106 | 9.3672 | 0.0825 | | 9.3672 | 0.0039 | 107 | 9.3594 | 0.0823 | | 9.3359 | 0.0039 | 108 | 9.3516 | 0.0822 | | 9.4062 | 0.0040 | 109 | 9.3438 | 0.0818 | | 9.3906 | 0.0040 | 110 | 9.3438 | 0.0816 | | 9.25 | 0.0040 | 111 | 9.3359 | 0.0816 | | 9.3281 | 0.0041 | 112 | 9.3281 | 0.0816 | | 9.375 | 0.0041 | 113 | 9.3203 | 0.0813 | | 9.3906 | 0.0041 | 114 | 9.3203 | 0.0812 | | 9.3203 | 0.0042 | 115 | 9.3125 | 0.0812 | | 9.3125 | 0.0042 | 116 | 9.3047 | 0.0811 | | 9.3359 | 0.0043 | 117 | 9.2969 | 0.0809 | | 9.2812 | 0.0043 | 118 | 9.2969 | 0.0808 | | 9.2031 | 0.0043 | 119 | 9.2891 | 0.0807 | | 9.2422 | 0.0044 | 120 | 9.2812 | 0.0808 | | 9.3047 | 0.0044 | 121 | 9.2812 | 0.0809 | | 9.2969 | 0.0044 | 122 | 9.2734 | 0.0810 | | 9.25 | 0.0045 | 123 | 9.2656 | 0.0815 | | 9.3281 | 0.0045 | 124 | 9.2578 | 0.0825 | | 9.2656 | 0.0045 | 125 | 9.2578 | 0.0836 | | 9.3047 | 0.0046 | 126 | 9.25 | 0.0845 | | 9.25 | 0.0046 | 127 | 9.2422 | 0.0850 | | 9.2969 | 0.0046 | 128 | 9.2344 | 0.0852 | | 9.3203 | 0.0047 | 129 | 9.2344 | 0.0853 | | 9.25 | 0.0047 | 130 | 9.2266 | 0.0853 | | 9.2422 | 0.0048 | 131 | 9.2188 | 0.0854 | | 9.1641 | 0.0048 | 132 | 9.2109 | 0.0855 | | 9.2109 | 0.0048 | 133 | 9.2109 | 0.0858 | | 9.2422 | 0.0049 | 134 | 9.2031 | 0.0860 | | 9.2188 | 0.0049 | 135 | 9.1953 | 0.0861 | | 9.3047 | 0.0049 | 136 | 9.1875 | 0.0861 | | 9.1641 | 0.0050 | 137 | 9.1875 | 0.0861 | | 9.2188 | 0.0050 | 138 | 9.1797 | 0.0859 | | 9.2422 | 0.0050 | 139 | 9.1719 | 0.0856 | | 9.2422 | 0.0051 | 140 | 9.1719 | 0.0855 | | 9.1484 | 0.0051 | 141 | 9.1641 | 0.0852 | | 9.2422 | 0.0052 | 142 | 9.1562 | 0.0851 | | 9.1953 | 0.0052 | 143 | 9.1484 | 0.0852 | | 9.1641 | 0.0052 | 144 | 9.1484 | 0.0853 | | 9.1875 | 0.0053 | 145 | 9.1406 | 0.0854 | | 9.1172 | 0.0053 | 146 | 9.1328 | 0.0855 | | 9.1094 | 0.0053 | 147 | 9.1328 | 0.0856 | | 9.1328 | 0.0054 | 148 | 9.125 | 0.0859 | | 9.1641 | 0.0054 | 149 | 9.1172 | 0.0863 | | 9.1641 | 0.0054 | 150 | 9.1094 | 0.0868 | | 9.1875 | 0.0055 | 151 | 9.1094 | 0.0873 | | 9.2031 | 0.0055 | 152 | 9.1016 | 0.0875 | | 9.0703 | 0.0056 | 153 | 9.0938 | 0.0880 | | 9.1484 | 0.0056 | 154 | 9.0859 | 0.0884 | | 9.0625 | 0.0056 | 155 | 9.0859 | 0.0888 | | 9.0781 | 0.0057 | 156 | 9.0781 | 0.0889 | | 9.0234 | 0.0057 | 157 | 9.0703 | 0.0892 | | 9.0781 | 0.0057 | 158 | 9.0703 | 0.0894 | | 9.0 | 0.0058 | 159 | 9.0625 | 0.0895 | | 9.0312 | 0.0058 | 160 | 9.0547 | 0.0896 | | 9.0391 | 0.0058 | 161 | 9.0547 | 0.0898 | | 9.0469 | 0.0059 | 162 | 9.0469 | 0.0901 | | 9.0859 | 0.0059 | 163 | 9.0391 | 0.0905 | | 9.0078 | 0.0060 | 164 | 9.0312 | 0.0908 | | 9.0156 | 0.0060 | 165 | 9.0312 | 0.0909 | | 9.0469 | 0.0060 | 166 | 9.0234 | 0.0909 | | 8.9219 | 0.0061 | 167 | 9.0234 | 0.0908 | | 9.0312 | 0.0061 | 168 | 9.0156 | 0.0907 | | 9.0938 | 0.0061 | 169 | 9.0078 | 0.0906 | | 9.0156 | 0.0062 | 170 | 9.0 | 0.0902 | | 9.0312 | 0.0062 | 171 | 9.0 | 0.0897 | | 9.0625 | 0.0062 | 172 | 8.9922 | 0.0893 | | 8.9844 | 0.0063 | 173 | 8.9844 | 0.0891 | | 9.0703 | 0.0063 | 174 | 8.9844 | 0.0894 | | 8.9609 | 0.0064 | 175 | 8.9766 | 0.0898 | | 8.9922 | 0.0064 | 176 | 8.9766 | 0.0905 | | 9.0234 | 0.0064 | 177 | 8.9688 | 0.0910 | | 9.0234 | 0.0065 | 178 | 8.9609 | 0.0915 | | 8.9219 | 0.0065 | 179 | 8.9531 | 0.0919 | | 9.0234 | 0.0065 | 180 | 8.9531 | 0.0920 | | 8.9375 | 0.0066 | 181 | 8.9453 | 0.0921 | | 8.9688 | 0.0066 | 182 | 8.9375 | 0.0919 | | 8.9375 | 0.0066 | 183 | 8.9375 | 0.0913 | | 9.0 | 0.0067 | 184 | 8.9297 | 0.0912 | | 8.9375 | 0.0067 | 185 | 8.9219 | 0.0913 | | 8.9609 | 0.0068 | 186 | 8.9219 | 0.0913 | | 8.9688 | 0.0068 | 187 | 8.9141 | 0.0917 | ### Framework versions - Transformers 4.41.2 - Pytorch 2.1.0a0+32f93b1 - Datasets 2.20.0 - Tokenizers 0.19.1