--- license: mit tags: - generated_from_trainer model-index: - name: gpt-neo-125m-neurallinguisticpioneers results: [] --- # gpt-neo-125m-neurallinguisticpioneers This model is a fine-tuned version of [EleutherAI/gpt-neo-125m](https://huggingface.co/EleutherAI/gpt-neo-125m) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.6584 ## 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: 3e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 1 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 5.8245 | 0.01 | 1 | 5.0320 | | 5.1946 | 0.01 | 2 | 4.2171 | | 4.1809 | 0.02 | 3 | 3.4349 | | 3.3553 | 0.02 | 4 | 2.7171 | | 2.185 | 0.03 | 5 | 2.0634 | | 1.9955 | 0.03 | 6 | 1.5786 | | 1.9371 | 0.04 | 7 | 1.2490 | | 1.4402 | 0.04 | 8 | 1.0349 | | 0.8763 | 0.05 | 9 | 0.9157 | | 0.8813 | 0.05 | 10 | 0.8550 | | 0.7723 | 0.06 | 11 | 0.8259 | | 0.7909 | 0.06 | 12 | 0.8052 | | 0.4889 | 0.07 | 13 | 0.7959 | | 0.7361 | 0.07 | 14 | 0.7891 | | 0.4922 | 0.08 | 15 | 0.7793 | | 0.5533 | 0.09 | 16 | 0.7675 | | 1.1071 | 0.09 | 17 | 0.7563 | | 0.7885 | 0.1 | 18 | 0.7480 | | 0.7701 | 0.1 | 19 | 0.7445 | | 0.6235 | 0.11 | 20 | 0.7447 | | 0.8623 | 0.11 | 21 | 0.7484 | | 0.665 | 0.12 | 22 | 0.7558 | | 0.6907 | 0.12 | 23 | 0.7573 | | 0.7143 | 0.13 | 24 | 0.7583 | | 0.7554 | 0.13 | 25 | 0.7599 | | 0.6228 | 0.14 | 26 | 0.7621 | | 0.8079 | 0.14 | 27 | 0.7612 | | 0.6974 | 0.15 | 28 | 0.7586 | | 0.8349 | 0.16 | 29 | 0.7541 | | 0.8251 | 0.16 | 30 | 0.7484 | | 0.687 | 0.17 | 31 | 0.7400 | | 0.8156 | 0.17 | 32 | 0.7280 | | 0.7693 | 0.18 | 33 | 0.7183 | | 0.5224 | 0.18 | 34 | 0.7096 | | 0.6345 | 0.19 | 35 | 0.7033 | | 0.6443 | 0.19 | 36 | 0.6979 | | 1.1552 | 0.2 | 37 | 0.6930 | | 0.7819 | 0.2 | 38 | 0.6897 | | 0.6277 | 0.21 | 39 | 0.6875 | | 0.5751 | 0.21 | 40 | 0.6862 | | 0.7169 | 0.22 | 41 | 0.6854 | | 0.7077 | 0.22 | 42 | 0.6842 | | 0.5667 | 0.23 | 43 | 0.6831 | | 0.9234 | 0.24 | 44 | 0.6822 | | 0.6332 | 0.24 | 45 | 0.6815 | | 0.865 | 0.25 | 46 | 0.6806 | | 0.5918 | 0.25 | 47 | 0.6797 | | 0.6196 | 0.26 | 48 | 0.6788 | | 0.7697 | 0.26 | 49 | 0.6778 | | 0.4448 | 0.27 | 50 | 0.6769 | | 0.7951 | 0.27 | 51 | 0.6760 | | 0.9171 | 0.28 | 52 | 0.6751 | | 0.7169 | 0.28 | 53 | 0.6745 | | 0.7001 | 0.29 | 54 | 0.6742 | | 0.7755 | 0.29 | 55 | 0.6742 | | 0.7426 | 0.3 | 56 | 0.6743 | | 0.6208 | 0.3 | 57 | 0.6742 | | 0.6962 | 0.31 | 58 | 0.6740 | | 0.3848 | 0.32 | 59 | 0.6739 | | 0.6986 | 0.32 | 60 | 0.6736 | | 0.6316 | 0.33 | 61 | 0.6734 | | 0.5988 | 0.33 | 62 | 0.6732 | | 0.6551 | 0.34 | 63 | 0.6729 | | 0.6102 | 0.34 | 64 | 0.6724 | | 0.7752 | 0.35 | 65 | 0.6718 | | 0.6145 | 0.35 | 66 | 0.6713 | | 0.6829 | 0.36 | 67 | 0.6709 | | 0.7952 | 0.36 | 68 | 0.6705 | | 0.5888 | 0.37 | 69 | 0.6702 | | 0.7763 | 0.37 | 70 | 0.6698 | | 0.6723 | 0.38 | 71 | 0.6694 | | 0.6429 | 0.39 | 72 | 0.6691 | | 1.0005 | 0.39 | 73 | 0.6688 | | 0.6184 | 0.4 | 74 | 0.6684 | | 0.7118 | 0.4 | 75 | 0.6682 | | 0.5414 | 0.41 | 76 | 0.6679 | | 0.6491 | 0.41 | 77 | 0.6676 | | 0.9418 | 0.42 | 78 | 0.6673 | | 0.7183 | 0.42 | 79 | 0.6670 | | 0.682 | 0.43 | 80 | 0.6668 | | 0.5946 | 0.43 | 81 | 0.6665 | | 0.6681 | 0.44 | 82 | 0.6662 | | 0.9125 | 0.44 | 83 | 0.6659 | | 0.6752 | 0.45 | 84 | 0.6657 | | 0.6908 | 0.45 | 85 | 0.6655 | | 0.5878 | 0.46 | 86 | 0.6653 | | 0.805 | 0.47 | 87 | 0.6651 | | 0.7584 | 0.47 | 88 | 0.6650 | | 0.6652 | 0.48 | 89 | 0.6649 | | 0.9363 | 0.48 | 90 | 0.6647 | | 0.6201 | 0.49 | 91 | 0.6646 | | 0.6827 | 0.49 | 92 | 0.6644 | | 0.8921 | 0.5 | 93 | 0.6643 | | 0.5194 | 0.5 | 94 | 0.6641 | | 0.9393 | 0.51 | 95 | 0.6639 | | 0.8484 | 0.51 | 96 | 0.6637 | | 0.5412 | 0.52 | 97 | 0.6635 | | 1.0085 | 0.52 | 98 | 0.6633 | | 0.5217 | 0.53 | 99 | 0.6632 | | 0.6137 | 0.53 | 100 | 0.6630 | | 0.5484 | 0.54 | 101 | 0.6629 | | 0.5827 | 0.55 | 102 | 0.6627 | | 0.3374 | 0.55 | 103 | 0.6629 | | 0.8269 | 0.56 | 104 | 0.6630 | | 0.8126 | 0.56 | 105 | 0.6630 | | 0.8088 | 0.57 | 106 | 0.6631 | | 0.5498 | 0.57 | 107 | 0.6632 | | 0.6787 | 0.58 | 108 | 0.6633 | | 0.8786 | 0.58 | 109 | 0.6633 | | 0.6237 | 0.59 | 110 | 0.6634 | | 0.6369 | 0.59 | 111 | 0.6634 | | 0.5629 | 0.6 | 112 | 0.6634 | | 0.4571 | 0.6 | 113 | 0.6635 | | 0.902 | 0.61 | 114 | 0.6634 | | 0.5153 | 0.61 | 115 | 0.6632 | | 0.9284 | 0.62 | 116 | 0.6629 | | 0.7149 | 0.63 | 117 | 0.6626 | | 0.5224 | 0.63 | 118 | 0.6623 | | 0.5969 | 0.64 | 119 | 0.6621 | | 0.655 | 0.64 | 120 | 0.6619 | | 0.6182 | 0.65 | 121 | 0.6619 | | 0.6564 | 0.65 | 122 | 0.6618 | | 0.6919 | 0.66 | 123 | 0.6618 | | 0.5894 | 0.66 | 124 | 0.6617 | | 0.4312 | 0.67 | 125 | 0.6617 | | 0.7523 | 0.67 | 126 | 0.6617 | | 0.7962 | 0.68 | 127 | 0.6617 | | 0.3758 | 0.68 | 128 | 0.6617 | | 0.7343 | 0.69 | 129 | 0.6617 | | 0.7569 | 0.7 | 130 | 0.6616 | | 0.4816 | 0.7 | 131 | 0.6616 | | 0.7127 | 0.71 | 132 | 0.6616 | | 0.4597 | 0.71 | 133 | 0.6616 | | 0.6429 | 0.72 | 134 | 0.6616 | | 0.6452 | 0.72 | 135 | 0.6616 | | 0.5815 | 0.73 | 136 | 0.6615 | | 0.743 | 0.73 | 137 | 0.6614 | | 0.5613 | 0.74 | 138 | 0.6612 | | 0.5038 | 0.74 | 139 | 0.6610 | | 0.797 | 0.75 | 140 | 0.6609 | | 0.6244 | 0.75 | 141 | 0.6608 | | 0.4257 | 0.76 | 142 | 0.6607 | | 0.6096 | 0.76 | 143 | 0.6606 | | 0.6566 | 0.77 | 144 | 0.6605 | | 0.4325 | 0.78 | 145 | 0.6604 | | 0.7307 | 0.78 | 146 | 0.6604 | | 0.7955 | 0.79 | 147 | 0.6603 | | 0.6972 | 0.79 | 148 | 0.6602 | | 0.7527 | 0.8 | 149 | 0.6602 | | 0.5718 | 0.8 | 150 | 0.6602 | | 0.8002 | 0.81 | 151 | 0.6602 | | 0.6643 | 0.81 | 152 | 0.6602 | | 0.7817 | 0.82 | 153 | 0.6602 | | 0.6829 | 0.82 | 154 | 0.6602 | | 0.8392 | 0.83 | 155 | 0.6601 | | 0.5246 | 0.83 | 156 | 0.6601 | | 0.6613 | 0.84 | 157 | 0.6601 | | 0.4456 | 0.84 | 158 | 0.6600 | | 0.4505 | 0.85 | 159 | 0.6600 | | 0.6184 | 0.86 | 160 | 0.6600 | | 0.6419 | 0.86 | 161 | 0.6599 | | 0.3138 | 0.87 | 162 | 0.6599 | | 0.5554 | 0.87 | 163 | 0.6598 | | 0.702 | 0.88 | 164 | 0.6597 | | 0.801 | 0.88 | 165 | 0.6595 | | 0.6689 | 0.89 | 166 | 0.6594 | | 0.5907 | 0.89 | 167 | 0.6593 | | 0.9349 | 0.9 | 168 | 0.6592 | | 0.7987 | 0.9 | 169 | 0.6591 | | 0.6379 | 0.91 | 170 | 0.6590 | | 0.5561 | 0.91 | 171 | 0.6589 | | 0.6637 | 0.92 | 172 | 0.6589 | | 0.5391 | 0.93 | 173 | 0.6588 | | 0.6578 | 0.93 | 174 | 0.6588 | | 0.7013 | 0.94 | 175 | 0.6587 | | 0.6868 | 0.94 | 176 | 0.6587 | | 0.6297 | 0.95 | 177 | 0.6586 | | 0.7349 | 0.95 | 178 | 0.6586 | | 0.8577 | 0.96 | 179 | 0.6585 | | 0.8536 | 0.96 | 180 | 0.6585 | | 0.4971 | 0.97 | 181 | 0.6585 | | 0.5129 | 0.97 | 182 | 0.6585 | | 0.7636 | 0.98 | 183 | 0.6585 | | 0.5111 | 0.98 | 184 | 0.6585 | | 0.7281 | 0.99 | 185 | 0.6585 | | 0.5653 | 0.99 | 186 | 0.6585 | | 0.7766 | 1.0 | 187 | 0.6584 | ### Framework versions - Transformers 4.28.0 - Pytorch 2.0.1+cu118 - Datasets 2.12.0 - Tokenizers 0.13.3