update model card README.md
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README.md
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| 1 |
+
---
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| 2 |
+
license: mit
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| 3 |
+
tags:
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+
- generated_from_trainer
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| 5 |
+
model-index:
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+
- name: gpt-neo-125m-neurallinguisticpioneers
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| 7 |
+
results: []
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| 8 |
+
---
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| 9 |
+
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| 10 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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| 11 |
+
should probably proofread and complete it, then remove this comment. -->
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| 12 |
+
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| 13 |
+
# gpt-neo-125m-neurallinguisticpioneers
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| 14 |
+
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| 15 |
+
This model is a fine-tuned version of [EleutherAI/gpt-neo-125m](https://huggingface.co/EleutherAI/gpt-neo-125m) on an unknown dataset.
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| 16 |
+
It achieves the following results on the evaluation set:
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| 17 |
+
- Loss: 0.6584
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| 18 |
+
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| 19 |
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## Model description
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| 20 |
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| 21 |
+
More information needed
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| 22 |
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## Intended uses & limitations
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| 24 |
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More information needed
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## Training and evaluation data
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| 28 |
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More information needed
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## Training procedure
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| 32 |
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| 33 |
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### Training hyperparameters
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| 34 |
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The following hyperparameters were used during training:
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| 36 |
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- learning_rate: 3e-05
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| 37 |
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- train_batch_size: 8
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| 38 |
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- eval_batch_size: 8
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| 39 |
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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| 41 |
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- lr_scheduler_type: linear
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- num_epochs: 1
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| 43 |
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| 44 |
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### Training results
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| 45 |
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| 46 |
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| Training Loss | Epoch | Step | Validation Loss |
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| 47 |
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|:-------------:|:-----:|:----:|:---------------:|
|
| 48 |
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| 5.8245 | 0.01 | 1 | 5.0320 |
|
| 49 |
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| 5.1946 | 0.01 | 2 | 4.2171 |
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| 50 |
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| 4.1809 | 0.02 | 3 | 3.4349 |
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| 51 |
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| 3.3553 | 0.02 | 4 | 2.7171 |
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| 52 |
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| 2.185 | 0.03 | 5 | 2.0634 |
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| 53 |
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| 1.9955 | 0.03 | 6 | 1.5786 |
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| 54 |
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| 1.9371 | 0.04 | 7 | 1.2490 |
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| 55 |
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| 1.4402 | 0.04 | 8 | 1.0349 |
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| 56 |
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| 0.8763 | 0.05 | 9 | 0.9157 |
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| 57 |
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| 0.8813 | 0.05 | 10 | 0.8550 |
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| 58 |
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| 0.7723 | 0.06 | 11 | 0.8259 |
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| 59 |
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| 0.7909 | 0.06 | 12 | 0.8052 |
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| 60 |
+
| 0.4889 | 0.07 | 13 | 0.7959 |
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| 61 |
+
| 0.7361 | 0.07 | 14 | 0.7891 |
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| 62 |
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| 0.4922 | 0.08 | 15 | 0.7793 |
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| 63 |
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| 0.5533 | 0.09 | 16 | 0.7675 |
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| 64 |
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| 1.1071 | 0.09 | 17 | 0.7563 |
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| 65 |
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| 0.7885 | 0.1 | 18 | 0.7480 |
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| 66 |
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| 0.7701 | 0.1 | 19 | 0.7445 |
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| 67 |
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| 0.6235 | 0.11 | 20 | 0.7447 |
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| 68 |
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| 0.8623 | 0.11 | 21 | 0.7484 |
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| 69 |
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| 0.665 | 0.12 | 22 | 0.7558 |
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| 70 |
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| 0.6907 | 0.12 | 23 | 0.7573 |
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| 71 |
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| 0.7143 | 0.13 | 24 | 0.7583 |
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| 72 |
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| 0.7554 | 0.13 | 25 | 0.7599 |
|
| 73 |
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| 0.6228 | 0.14 | 26 | 0.7621 |
|
| 74 |
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| 0.8079 | 0.14 | 27 | 0.7612 |
|
| 75 |
+
| 0.6974 | 0.15 | 28 | 0.7586 |
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| 76 |
+
| 0.8349 | 0.16 | 29 | 0.7541 |
|
| 77 |
+
| 0.8251 | 0.16 | 30 | 0.7484 |
|
| 78 |
+
| 0.687 | 0.17 | 31 | 0.7400 |
|
| 79 |
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| 0.8156 | 0.17 | 32 | 0.7280 |
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| 80 |
+
| 0.7693 | 0.18 | 33 | 0.7183 |
|
| 81 |
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| 0.5224 | 0.18 | 34 | 0.7096 |
|
| 82 |
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| 0.6345 | 0.19 | 35 | 0.7033 |
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| 83 |
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| 0.6443 | 0.19 | 36 | 0.6979 |
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| 84 |
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| 1.1552 | 0.2 | 37 | 0.6930 |
|
| 85 |
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| 0.7819 | 0.2 | 38 | 0.6897 |
|
| 86 |
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| 0.6277 | 0.21 | 39 | 0.6875 |
|
| 87 |
+
| 0.5751 | 0.21 | 40 | 0.6862 |
|
| 88 |
+
| 0.7169 | 0.22 | 41 | 0.6854 |
|
| 89 |
+
| 0.7077 | 0.22 | 42 | 0.6842 |
|
| 90 |
+
| 0.5667 | 0.23 | 43 | 0.6831 |
|
| 91 |
+
| 0.9234 | 0.24 | 44 | 0.6822 |
|
| 92 |
+
| 0.6332 | 0.24 | 45 | 0.6815 |
|
| 93 |
+
| 0.865 | 0.25 | 46 | 0.6806 |
|
| 94 |
+
| 0.5918 | 0.25 | 47 | 0.6797 |
|
| 95 |
+
| 0.6196 | 0.26 | 48 | 0.6788 |
|
| 96 |
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| 0.7697 | 0.26 | 49 | 0.6778 |
|
| 97 |
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| 0.4448 | 0.27 | 50 | 0.6769 |
|
| 98 |
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| 0.7951 | 0.27 | 51 | 0.6760 |
|
| 99 |
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| 0.9171 | 0.28 | 52 | 0.6751 |
|
| 100 |
+
| 0.7169 | 0.28 | 53 | 0.6745 |
|
| 101 |
+
| 0.7001 | 0.29 | 54 | 0.6742 |
|
| 102 |
+
| 0.7755 | 0.29 | 55 | 0.6742 |
|
| 103 |
+
| 0.7426 | 0.3 | 56 | 0.6743 |
|
| 104 |
+
| 0.6208 | 0.3 | 57 | 0.6742 |
|
| 105 |
+
| 0.6962 | 0.31 | 58 | 0.6740 |
|
| 106 |
+
| 0.3848 | 0.32 | 59 | 0.6739 |
|
| 107 |
+
| 0.6986 | 0.32 | 60 | 0.6736 |
|
| 108 |
+
| 0.6316 | 0.33 | 61 | 0.6734 |
|
| 109 |
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| 0.5988 | 0.33 | 62 | 0.6732 |
|
| 110 |
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| 0.6551 | 0.34 | 63 | 0.6729 |
|
| 111 |
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| 0.6102 | 0.34 | 64 | 0.6724 |
|
| 112 |
+
| 0.7752 | 0.35 | 65 | 0.6718 |
|
| 113 |
+
| 0.6145 | 0.35 | 66 | 0.6713 |
|
| 114 |
+
| 0.6829 | 0.36 | 67 | 0.6709 |
|
| 115 |
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| 0.7952 | 0.36 | 68 | 0.6705 |
|
| 116 |
+
| 0.5888 | 0.37 | 69 | 0.6702 |
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| 117 |
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| 0.7763 | 0.37 | 70 | 0.6698 |
|
| 118 |
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| 0.6723 | 0.38 | 71 | 0.6694 |
|
| 119 |
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| 0.6429 | 0.39 | 72 | 0.6691 |
|
| 120 |
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| 1.0005 | 0.39 | 73 | 0.6688 |
|
| 121 |
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| 0.6184 | 0.4 | 74 | 0.6684 |
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| 122 |
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| 0.7118 | 0.4 | 75 | 0.6682 |
|
| 123 |
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| 0.5414 | 0.41 | 76 | 0.6679 |
|
| 124 |
+
| 0.6491 | 0.41 | 77 | 0.6676 |
|
| 125 |
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| 0.9418 | 0.42 | 78 | 0.6673 |
|
| 126 |
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| 0.7183 | 0.42 | 79 | 0.6670 |
|
| 127 |
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| 0.682 | 0.43 | 80 | 0.6668 |
|
| 128 |
+
| 0.5946 | 0.43 | 81 | 0.6665 |
|
| 129 |
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| 0.6681 | 0.44 | 82 | 0.6662 |
|
| 130 |
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| 0.9125 | 0.44 | 83 | 0.6659 |
|
| 131 |
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| 0.6752 | 0.45 | 84 | 0.6657 |
|
| 132 |
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| 0.6908 | 0.45 | 85 | 0.6655 |
|
| 133 |
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| 0.5878 | 0.46 | 86 | 0.6653 |
|
| 134 |
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| 0.805 | 0.47 | 87 | 0.6651 |
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| 135 |
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| 0.7584 | 0.47 | 88 | 0.6650 |
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| 136 |
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| 0.6652 | 0.48 | 89 | 0.6649 |
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| 137 |
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| 0.9363 | 0.48 | 90 | 0.6647 |
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| 138 |
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| 0.6201 | 0.49 | 91 | 0.6646 |
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| 139 |
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| 0.6827 | 0.49 | 92 | 0.6644 |
|
| 140 |
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| 0.8921 | 0.5 | 93 | 0.6643 |
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| 141 |
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| 0.5194 | 0.5 | 94 | 0.6641 |
|
| 142 |
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| 0.9393 | 0.51 | 95 | 0.6639 |
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| 143 |
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| 0.8484 | 0.51 | 96 | 0.6637 |
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| 144 |
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| 0.5412 | 0.52 | 97 | 0.6635 |
|
| 145 |
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| 1.0085 | 0.52 | 98 | 0.6633 |
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| 146 |
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| 0.5217 | 0.53 | 99 | 0.6632 |
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| 147 |
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| 0.6137 | 0.53 | 100 | 0.6630 |
|
| 148 |
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| 0.5484 | 0.54 | 101 | 0.6629 |
|
| 149 |
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| 0.5827 | 0.55 | 102 | 0.6627 |
|
| 150 |
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| 0.3374 | 0.55 | 103 | 0.6629 |
|
| 151 |
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| 0.8269 | 0.56 | 104 | 0.6630 |
|
| 152 |
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| 0.8126 | 0.56 | 105 | 0.6630 |
|
| 153 |
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| 0.8088 | 0.57 | 106 | 0.6631 |
|
| 154 |
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| 0.5498 | 0.57 | 107 | 0.6632 |
|
| 155 |
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| 0.6787 | 0.58 | 108 | 0.6633 |
|
| 156 |
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| 0.8786 | 0.58 | 109 | 0.6633 |
|
| 157 |
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| 0.6237 | 0.59 | 110 | 0.6634 |
|
| 158 |
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| 0.6369 | 0.59 | 111 | 0.6634 |
|
| 159 |
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| 0.5629 | 0.6 | 112 | 0.6634 |
|
| 160 |
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| 0.4571 | 0.6 | 113 | 0.6635 |
|
| 161 |
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| 0.902 | 0.61 | 114 | 0.6634 |
|
| 162 |
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| 0.5153 | 0.61 | 115 | 0.6632 |
|
| 163 |
+
| 0.9284 | 0.62 | 116 | 0.6629 |
|
| 164 |
+
| 0.7149 | 0.63 | 117 | 0.6626 |
|
| 165 |
+
| 0.5224 | 0.63 | 118 | 0.6623 |
|
| 166 |
+
| 0.5969 | 0.64 | 119 | 0.6621 |
|
| 167 |
+
| 0.655 | 0.64 | 120 | 0.6619 |
|
| 168 |
+
| 0.6182 | 0.65 | 121 | 0.6619 |
|
| 169 |
+
| 0.6564 | 0.65 | 122 | 0.6618 |
|
| 170 |
+
| 0.6919 | 0.66 | 123 | 0.6618 |
|
| 171 |
+
| 0.5894 | 0.66 | 124 | 0.6617 |
|
| 172 |
+
| 0.4312 | 0.67 | 125 | 0.6617 |
|
| 173 |
+
| 0.7523 | 0.67 | 126 | 0.6617 |
|
| 174 |
+
| 0.7962 | 0.68 | 127 | 0.6617 |
|
| 175 |
+
| 0.3758 | 0.68 | 128 | 0.6617 |
|
| 176 |
+
| 0.7343 | 0.69 | 129 | 0.6617 |
|
| 177 |
+
| 0.7569 | 0.7 | 130 | 0.6616 |
|
| 178 |
+
| 0.4816 | 0.7 | 131 | 0.6616 |
|
| 179 |
+
| 0.7127 | 0.71 | 132 | 0.6616 |
|
| 180 |
+
| 0.4597 | 0.71 | 133 | 0.6616 |
|
| 181 |
+
| 0.6429 | 0.72 | 134 | 0.6616 |
|
| 182 |
+
| 0.6452 | 0.72 | 135 | 0.6616 |
|
| 183 |
+
| 0.5815 | 0.73 | 136 | 0.6615 |
|
| 184 |
+
| 0.743 | 0.73 | 137 | 0.6614 |
|
| 185 |
+
| 0.5613 | 0.74 | 138 | 0.6612 |
|
| 186 |
+
| 0.5038 | 0.74 | 139 | 0.6610 |
|
| 187 |
+
| 0.797 | 0.75 | 140 | 0.6609 |
|
| 188 |
+
| 0.6244 | 0.75 | 141 | 0.6608 |
|
| 189 |
+
| 0.4257 | 0.76 | 142 | 0.6607 |
|
| 190 |
+
| 0.6096 | 0.76 | 143 | 0.6606 |
|
| 191 |
+
| 0.6566 | 0.77 | 144 | 0.6605 |
|
| 192 |
+
| 0.4325 | 0.78 | 145 | 0.6604 |
|
| 193 |
+
| 0.7307 | 0.78 | 146 | 0.6604 |
|
| 194 |
+
| 0.7955 | 0.79 | 147 | 0.6603 |
|
| 195 |
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| 0.6972 | 0.79 | 148 | 0.6602 |
|
| 196 |
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| 0.7527 | 0.8 | 149 | 0.6602 |
|
| 197 |
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| 0.5718 | 0.8 | 150 | 0.6602 |
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| 198 |
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| 0.8002 | 0.81 | 151 | 0.6602 |
|
| 199 |
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| 0.6643 | 0.81 | 152 | 0.6602 |
|
| 200 |
+
| 0.7817 | 0.82 | 153 | 0.6602 |
|
| 201 |
+
| 0.6829 | 0.82 | 154 | 0.6602 |
|
| 202 |
+
| 0.8392 | 0.83 | 155 | 0.6601 |
|
| 203 |
+
| 0.5246 | 0.83 | 156 | 0.6601 |
|
| 204 |
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| 0.6613 | 0.84 | 157 | 0.6601 |
|
| 205 |
+
| 0.4456 | 0.84 | 158 | 0.6600 |
|
| 206 |
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| 0.4505 | 0.85 | 159 | 0.6600 |
|
| 207 |
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| 0.6184 | 0.86 | 160 | 0.6600 |
|
| 208 |
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| 0.6419 | 0.86 | 161 | 0.6599 |
|
| 209 |
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| 0.3138 | 0.87 | 162 | 0.6599 |
|
| 210 |
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| 0.5554 | 0.87 | 163 | 0.6598 |
|
| 211 |
+
| 0.702 | 0.88 | 164 | 0.6597 |
|
| 212 |
+
| 0.801 | 0.88 | 165 | 0.6595 |
|
| 213 |
+
| 0.6689 | 0.89 | 166 | 0.6594 |
|
| 214 |
+
| 0.5907 | 0.89 | 167 | 0.6593 |
|
| 215 |
+
| 0.9349 | 0.9 | 168 | 0.6592 |
|
| 216 |
+
| 0.7987 | 0.9 | 169 | 0.6591 |
|
| 217 |
+
| 0.6379 | 0.91 | 170 | 0.6590 |
|
| 218 |
+
| 0.5561 | 0.91 | 171 | 0.6589 |
|
| 219 |
+
| 0.6637 | 0.92 | 172 | 0.6589 |
|
| 220 |
+
| 0.5391 | 0.93 | 173 | 0.6588 |
|
| 221 |
+
| 0.6578 | 0.93 | 174 | 0.6588 |
|
| 222 |
+
| 0.7013 | 0.94 | 175 | 0.6587 |
|
| 223 |
+
| 0.6868 | 0.94 | 176 | 0.6587 |
|
| 224 |
+
| 0.6297 | 0.95 | 177 | 0.6586 |
|
| 225 |
+
| 0.7349 | 0.95 | 178 | 0.6586 |
|
| 226 |
+
| 0.8577 | 0.96 | 179 | 0.6585 |
|
| 227 |
+
| 0.8536 | 0.96 | 180 | 0.6585 |
|
| 228 |
+
| 0.4971 | 0.97 | 181 | 0.6585 |
|
| 229 |
+
| 0.5129 | 0.97 | 182 | 0.6585 |
|
| 230 |
+
| 0.7636 | 0.98 | 183 | 0.6585 |
|
| 231 |
+
| 0.5111 | 0.98 | 184 | 0.6585 |
|
| 232 |
+
| 0.7281 | 0.99 | 185 | 0.6585 |
|
| 233 |
+
| 0.5653 | 0.99 | 186 | 0.6585 |
|
| 234 |
+
| 0.7766 | 1.0 | 187 | 0.6584 |
|
| 235 |
+
|
| 236 |
+
|
| 237 |
+
### Framework versions
|
| 238 |
+
|
| 239 |
+
- Transformers 4.28.0
|
| 240 |
+
- Pytorch 2.0.1+cu118
|
| 241 |
+
- Datasets 2.12.0
|
| 242 |
+
- Tokenizers 0.13.3
|