End of training
Browse files- README.md +127 -127
- model.safetensors +1 -1
- training_args.bin +1 -1
README.md
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@@ -4,10 +4,10 @@ base_model: klue/roberta-small
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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model-index:
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- name: roberta-small-hangul-2-hanja
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results: []
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@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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This model is a fine-tuned version of [klue/roberta-small](https://huggingface.co/klue/roberta-small) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0352
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- Precision: 0.9894
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- Recall: 0.9911
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- F1: 0.9902
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- Accuracy: 0.9956
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## Model description
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@@ -82,129 +82,129 @@ The following hyperparameters were used during training:
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| 0.0526 | 25.0 | 12050 | 0.9944 | 0.9926 | 0.0452 | 0.9926 | 0.9926 |
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| 83 |
| 0.0468 | 26.0 | 12532 | 0.9947 | 0.9933 | 0.0423 | 0.9926 | 0.9940 |
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| 0.0419 | 27.0 | 13014 | 0.9960 | 0.9945 | 0.0299 | 0.9943 | 0.9947 |
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-
| 0.0419 | 28.0 | 13496 | 0.
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-
| 0.0382 | 29.0 | 13978 | 0.
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| 87 |
-
| 0.0346 | 30.0 | 14460 | 0.
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| 88 |
-
| 0.0313 | 31.0 | 14942 | 0.
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| 89 |
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| 0.0286 | 32.0 | 15424 | 0.
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| 90 |
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| 0.026 | 33.0 | 15906 | 0.
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| 91 |
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| 0.0234 | 34.0 | 16388 | 0.
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| 92 |
-
| 0.0217 | 35.0 | 16870 | 0.
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| 93 |
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| 0.0198 | 36.0 | 17352 | 0.
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| 0.0178 | 37.0 | 17834 | 0.
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| 0.0167 | 38.0 | 18316 | 0.
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| 96 |
-
| 0.0149 | 39.0 | 18798 | 0.
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| 97 |
-
| 0.0137 | 40.0 | 19280 | 0.
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| 98 |
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| 0.013 | 41.0 | 19762 | 0.
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| 99 |
-
| 0.0115 | 42.0 | 20244 | 0.
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| 100 |
-
| 0.0107 | 43.0 | 20726 | 0.
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| 101 |
-
| 0.0098 | 44.0 | 21208 | 0.
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| 102 |
-
| 0.009 | 45.0 | 21690 | 0.
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| 103 |
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| 0.0081 | 46.0 | 22172 | 0.
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| 104 |
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| 0.0075 | 47.0 | 22654 | 0.
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| 105 |
-
| 0.0069 | 48.0 | 23136 | 0.
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| 106 |
-
| 0.0063 | 49.0 | 23618 | 0.
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| 107 |
-
| 0.0055 | 50.0 | 24100 | 0.
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| 108 |
-
| 0.0052 | 51.0 | 24582 | 0.
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| 109 |
-
| 0.0048 | 52.0 | 25064 | 0.
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| 110 |
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| 0.0044 | 53.0 | 25546 | 0.
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| 111 |
-
| 0.0039 | 54.0 | 26028 | 0.
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| 112 |
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| 0.0037 | 55.0 | 26510 | 0.
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| 113 |
-
| 0.0037 | 56.0 | 26992 | 0.
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| 114 |
-
| 0.0032 | 57.0 | 27474 | 0.
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| 115 |
-
| 0.003 | 58.0 | 27956 | 0.
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| 116 |
-
| 0.0027 | 59.0 | 28438 | 0.
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| 117 |
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| 0.0024 | 60.0 | 28920 | 0.
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| 118 |
-
| 0.0022 | 61.0 | 29402 | 0.
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| 119 |
-
| 0.0021 | 62.0 | 29884 | 0.
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| 120 |
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| 0.0019 | 63.0 | 30366 | 0.
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| 121 |
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| 0.0017 | 64.0 | 30848 | 0.
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| 122 |
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| 0.0015 | 65.0 | 31330 | 0.
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| 123 |
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| 0.0014 | 66.0 | 31812 | 0.
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| 124 |
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| 0.0012 | 67.0 | 32294 | 0.
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| 125 |
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| 0.0012 | 68.0 | 32776 | 0.
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| 126 |
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| 0.0011 | 69.0 | 33258 | 0.
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| 127 |
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| 0.001 | 70.0 | 33740 | 0.
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| 128 |
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| 0.001 | 71.0 | 34222 | 0.
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| 129 |
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| 0.0008 | 72.0 | 34704 | 0.
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| 0.0008 | 73.0 | 35186 | 0.
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| 0.0007 | 74.0 | 35668 | 0.
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| 0.0007 | 75.0 | 36150 | 0.
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| 0.0007 | 76.0 | 36632 | 0.
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| 0.0006 | 77.0 | 37114 | 0.
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| 0.0006 | 78.0 | 37596 | 0.
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| 0.0005 | 79.0 | 38078 | 0.
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| 0.0005 | 80.0 | 38560 | 0.
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| 0.0004 | 81.0 | 39042 | 0.
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| 0.0004 | 82.0 | 39524 | 0.
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| 0.0005 | 83.0 | 40006 | 0.
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| 0.0005 | 84.0 | 40488 | 0.
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| 0.0004 | 85.0 | 40970 | 0.
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| 0.0003 | 86.0 | 41452 | 0.
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| 0.0003 | 87.0 | 41934 | 0.
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| 0.0003 | 88.0 | 42416 | 0.
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| 0.0003 | 89.0 | 42898 | 0.
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| 0.0003 | 90.0 | 43380 | 0.
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| 0.0003 | 91.0 | 43862 | 0.
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| 149 |
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| 0.0003 | 92.0 | 44344 | 0.
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| 0.0002 | 93.0 | 44826 | 0.
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| 0.0003 | 94.0 | 45308 | 0.
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| 152 |
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| 0.0002 | 95.0 | 45790 | 0.
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| 0.0002 | 96.0 | 46272 | 0.
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| 0.0002 | 97.0 | 46754 | 0.
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| 0.0002 | 98.0 | 47236 | 0.
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| 0.0002 | 99.0 | 47718 | 0.
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| 0.0002 | 100.0 | 48200 | 0.
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| 0.0002 | 101.0 | 48682 | 0.
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| 0.0002 | 102.0 | 49164 | 0.
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| 0.0002 | 103.0 | 49646 | 0.
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| 0.0001 | 104.0 | 50128 | 0.
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| 0.0002 | 105.0 | 50610 | 0.
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| 0.0002 | 106.0 | 51092 | 0.
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| 0.0002 | 107.0 | 51574 | 0.
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| 0.0002 | 108.0 | 52056 | 0.
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| 0.0001 | 109.0 | 52538 | 0.
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| 0.0001 | 110.0 | 53020 | 0.
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| 0.0001 | 111.0 | 53502 | 0.
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| 0.0001 | 112.0 | 53984 | 0.
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| 0.0001 | 113.0 | 54466 | 0.
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| 0.0001 | 114.0 | 54948 | 0.
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| 0.0001 | 115.0 | 55430 | 0.
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| 0.0001 | 116.0 | 55912 | 0.
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| 0.0001 | 117.0 | 56394 | 0.
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| 0.0001 | 118.0 | 56876 | 0.
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| 0.0001 | 119.0 | 57358 | 0.
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| 0.0001 | 120.0 | 57840 | 0.
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| 0.0001 | 121.0 | 58322 | 0.
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| 0.0001 | 122.0 | 58804 | 0.
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| 0.0001 | 123.0 | 59286 | 0.
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| 0.0001 | 124.0 | 59768 | 0.
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| 0.0001 | 125.0 | 60250 | 0.
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| 0.0001 | 126.0 | 60732 | 0.
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| 0.0001 | 127.0 | 61214 | 0.
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| 0.0001 | 128.0 | 61696 | 0.
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| 0.0001 | 129.0 | 62178 | 0.
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| 0.0001 | 130.0 | 62660 | 0.
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| 0.0001 | 131.0 | 63142 | 0.
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| 0.0001 | 132.0 | 63624 | 0.
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| 0.0001 | 133.0 | 64106 | 0.
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| 0.0001 | 134.0 | 64588 | 0.
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| 0.0001 | 135.0 | 65070 | 0.
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| 0.0001 | 136.0 | 65552 | 0.
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| 0.0 | 137.0 | 66034 | 0.
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| 0.0001 | 138.0 | 66516 | 0.
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| 0.0001 | 139.0 | 66998 | 0.
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| 0.0001 | 140.0 | 67480 | 0.
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| 0.0001 | 141.0 | 67962 | 0.
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| 0.0001 | 142.0 | 68444 | 0.
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| 0.0001 | 143.0 | 68926 | 0.
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| 0.0 | 144.0 | 69408 | 0.
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| 0.0 | 145.0 | 69890 | 0.
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| 0.0001 | 146.0 | 70372 | 0.
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| 0.0001 | 147.0 | 70854 | 0.
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| 0.0 | 148.0 | 71336 | 0.
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| 0.0 | 149.0 | 71818 | 0.
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| 0.0 | 150.0 | 72300 | 0.
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### Framework versions
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|
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tags:
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- generated_from_trainer
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metrics:
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+
- accuracy
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+
- f1
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- precision
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- recall
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model-index:
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| 12 |
- name: roberta-small-hangul-2-hanja
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results: []
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This model is a fine-tuned version of [klue/roberta-small](https://huggingface.co/klue/roberta-small) on the None dataset.
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| 22 |
It achieves the following results on the evaluation set:
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| 23 |
+
- Accuracy: 0.9956
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| 24 |
+
- F1: 0.9902
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| 25 |
- Loss: 0.0352
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| 26 |
- Precision: 0.9894
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- Recall: 0.9911
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## Model description
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| 30 |
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| 82 |
| 0.0526 | 25.0 | 12050 | 0.9944 | 0.9926 | 0.0452 | 0.9926 | 0.9926 |
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| 83 |
| 0.0468 | 26.0 | 12532 | 0.9947 | 0.9933 | 0.0423 | 0.9926 | 0.9940 |
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| 84 |
| 0.0419 | 27.0 | 13014 | 0.9960 | 0.9945 | 0.0299 | 0.9943 | 0.9947 |
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| 85 |
+
| 0.0419 | 28.0 | 13496 | 0.9959 | 0.9934 | 0.0352 | 0.9929 | 0.9940 |
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| 86 |
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| 0.0382 | 29.0 | 13978 | 0.9964 | 0.9961 | 0.0342 | 0.9954 | 0.9968 |
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| 87 |
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| 0.0346 | 30.0 | 14460 | 0.9955 | 0.9940 | 0.0335 | 0.9933 | 0.9947 |
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| 88 |
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| 0.0313 | 31.0 | 14942 | 0.9957 | 0.9938 | 0.0318 | 0.9929 | 0.9947 |
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| 89 |
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| 0.0286 | 32.0 | 15424 | 0.9958 | 0.9943 | 0.0310 | 0.9936 | 0.9950 |
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| 90 |
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| 0.026 | 33.0 | 15906 | 0.9961 | 0.9950 | 0.0304 | 0.9943 | 0.9957 |
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| 91 |
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| 0.0234 | 34.0 | 16388 | 0.9960 | 0.9940 | 0.0292 | 0.9933 | 0.9947 |
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| 92 |
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| 0.0217 | 35.0 | 16870 | 0.9957 | 0.9941 | 0.0279 | 0.9933 | 0.9950 |
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| 93 |
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| 0.0198 | 36.0 | 17352 | 0.9958 | 0.9927 | 0.0272 | 0.9922 | 0.9933 |
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| 94 |
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| 0.0178 | 37.0 | 17834 | 0.9959 | 0.9933 | 0.0264 | 0.9926 | 0.9940 |
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| 95 |
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| 0.0167 | 38.0 | 18316 | 0.9958 | 0.9931 | 0.0266 | 0.9922 | 0.9940 |
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| 96 |
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| 0.0149 | 39.0 | 18798 | 0.9960 | 0.9931 | 0.0262 | 0.9922 | 0.9940 |
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| 97 |
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| 0.0137 | 40.0 | 19280 | 0.9956 | 0.9925 | 0.0255 | 0.9918 | 0.9933 |
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| 98 |
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| 0.013 | 41.0 | 19762 | 0.9958 | 0.9927 | 0.0253 | 0.9918 | 0.9936 |
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| 99 |
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| 0.0115 | 42.0 | 20244 | 0.9959 | 0.9918 | 0.0250 | 0.9915 | 0.9922 |
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| 100 |
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| 0.0107 | 43.0 | 20726 | 0.9957 | 0.9920 | 0.0258 | 0.9911 | 0.9929 |
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| 101 |
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| 0.0098 | 44.0 | 21208 | 0.9959 | 0.9931 | 0.0248 | 0.9922 | 0.9940 |
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| 102 |
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| 0.009 | 45.0 | 21690 | 0.9960 | 0.9920 | 0.0254 | 0.9911 | 0.9929 |
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| 103 |
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| 0.0081 | 46.0 | 22172 | 0.9959 | 0.9925 | 0.0258 | 0.9918 | 0.9933 |
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| 104 |
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| 0.0075 | 47.0 | 22654 | 0.9956 | 0.9915 | 0.0251 | 0.9904 | 0.9925 |
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| 105 |
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| 0.0069 | 48.0 | 23136 | 0.9956 | 0.9913 | 0.0256 | 0.9904 | 0.9922 |
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| 106 |
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| 0.0063 | 49.0 | 23618 | 0.9955 | 0.9906 | 0.0262 | 0.9894 | 0.9918 |
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| 107 |
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| 0.0055 | 50.0 | 24100 | 0.9959 | 0.9913 | 0.0254 | 0.9904 | 0.9922 |
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| 108 |
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| 0.0052 | 51.0 | 24582 | 0.9956 | 0.9911 | 0.0255 | 0.9901 | 0.9922 |
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| 109 |
+
| 0.0048 | 52.0 | 25064 | 0.9958 | 0.9910 | 0.0256 | 0.9901 | 0.9918 |
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| 110 |
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| 0.0044 | 53.0 | 25546 | 0.9954 | 0.9892 | 0.0276 | 0.9883 | 0.9901 |
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| 111 |
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| 0.0039 | 54.0 | 26028 | 0.9955 | 0.9897 | 0.0271 | 0.9890 | 0.9904 |
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| 112 |
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| 0.0037 | 55.0 | 26510 | 0.9957 | 0.9897 | 0.0275 | 0.9887 | 0.9908 |
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| 113 |
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| 0.0037 | 56.0 | 26992 | 0.9957 | 0.9910 | 0.0273 | 0.9901 | 0.9918 |
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| 114 |
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| 0.0032 | 57.0 | 27474 | 0.9960 | 0.9910 | 0.0270 | 0.9901 | 0.9918 |
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| 115 |
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| 0.003 | 58.0 | 27956 | 0.9955 | 0.9904 | 0.0284 | 0.9890 | 0.9918 |
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| 116 |
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| 0.0027 | 59.0 | 28438 | 0.9956 | 0.9904 | 0.0287 | 0.9890 | 0.9918 |
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| 117 |
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| 0.0024 | 60.0 | 28920 | 0.9955 | 0.9892 | 0.0290 | 0.9876 | 0.9908 |
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| 118 |
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| 0.0022 | 61.0 | 29402 | 0.9958 | 0.9910 | 0.0286 | 0.9901 | 0.9918 |
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| 119 |
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| 0.0021 | 62.0 | 29884 | 0.9959 | 0.9913 | 0.0286 | 0.9904 | 0.9922 |
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| 120 |
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| 0.0019 | 63.0 | 30366 | 0.9954 | 0.9897 | 0.0325 | 0.9883 | 0.9911 |
|
| 121 |
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| 0.0017 | 64.0 | 30848 | 0.9957 | 0.9906 | 0.0295 | 0.9897 | 0.9915 |
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| 122 |
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| 0.0015 | 65.0 | 31330 | 0.9958 | 0.9915 | 0.0289 | 0.9908 | 0.9922 |
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| 123 |
+
| 0.0014 | 66.0 | 31812 | 0.9957 | 0.9911 | 0.0303 | 0.9901 | 0.9922 |
|
| 124 |
+
| 0.0012 | 67.0 | 32294 | 0.9956 | 0.9904 | 0.0306 | 0.9890 | 0.9918 |
|
| 125 |
+
| 0.0012 | 68.0 | 32776 | 0.9955 | 0.9899 | 0.0312 | 0.9887 | 0.9911 |
|
| 126 |
+
| 0.0011 | 69.0 | 33258 | 0.9956 | 0.9897 | 0.0310 | 0.9883 | 0.9911 |
|
| 127 |
+
| 0.001 | 70.0 | 33740 | 0.9957 | 0.9895 | 0.0309 | 0.9883 | 0.9908 |
|
| 128 |
+
| 0.001 | 71.0 | 34222 | 0.9957 | 0.9901 | 0.0322 | 0.9897 | 0.9904 |
|
| 129 |
+
| 0.0008 | 72.0 | 34704 | 0.9958 | 0.9901 | 0.0323 | 0.9894 | 0.9908 |
|
| 130 |
+
| 0.0008 | 73.0 | 35186 | 0.9956 | 0.9897 | 0.0312 | 0.9890 | 0.9904 |
|
| 131 |
+
| 0.0007 | 74.0 | 35668 | 0.9957 | 0.9901 | 0.0327 | 0.9894 | 0.9908 |
|
| 132 |
+
| 0.0007 | 75.0 | 36150 | 0.9958 | 0.9911 | 0.0315 | 0.9904 | 0.9918 |
|
| 133 |
+
| 0.0007 | 76.0 | 36632 | 0.9957 | 0.9911 | 0.0318 | 0.9901 | 0.9922 |
|
| 134 |
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| 0.0006 | 77.0 | 37114 | 0.9958 | 0.9911 | 0.0314 | 0.9901 | 0.9922 |
|
| 135 |
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| 0.0006 | 78.0 | 37596 | 0.9956 | 0.9904 | 0.0325 | 0.9890 | 0.9918 |
|
| 136 |
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| 0.0005 | 79.0 | 38078 | 0.9955 | 0.9894 | 0.0318 | 0.9880 | 0.9908 |
|
| 137 |
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| 0.0005 | 80.0 | 38560 | 0.9957 | 0.9904 | 0.0315 | 0.9901 | 0.9908 |
|
| 138 |
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| 0.0004 | 81.0 | 39042 | 0.9958 | 0.9897 | 0.0321 | 0.9897 | 0.9897 |
|
| 139 |
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| 0.0004 | 82.0 | 39524 | 0.9952 | 0.9895 | 0.0340 | 0.9883 | 0.9908 |
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| 140 |
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| 0.0005 | 83.0 | 40006 | 0.9956 | 0.9915 | 0.0317 | 0.9908 | 0.9922 |
|
| 141 |
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| 0.0005 | 84.0 | 40488 | 0.9955 | 0.9901 | 0.0324 | 0.9887 | 0.9915 |
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| 142 |
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| 0.0004 | 85.0 | 40970 | 0.9956 | 0.9910 | 0.0320 | 0.9901 | 0.9918 |
|
| 143 |
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| 0.0003 | 86.0 | 41452 | 0.9957 | 0.9918 | 0.0324 | 0.9911 | 0.9925 |
|
| 144 |
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| 0.0003 | 87.0 | 41934 | 0.9959 | 0.9915 | 0.0308 | 0.9908 | 0.9922 |
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| 145 |
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| 0.0003 | 88.0 | 42416 | 0.9956 | 0.9913 | 0.0337 | 0.9904 | 0.9922 |
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| 146 |
+
| 0.0003 | 89.0 | 42898 | 0.9956 | 0.9913 | 0.0330 | 0.9904 | 0.9922 |
|
| 147 |
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| 0.0003 | 90.0 | 43380 | 0.9956 | 0.9890 | 0.0330 | 0.9876 | 0.9904 |
|
| 148 |
+
| 0.0003 | 91.0 | 43862 | 0.9957 | 0.9911 | 0.0341 | 0.9901 | 0.9922 |
|
| 149 |
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| 0.0003 | 92.0 | 44344 | 0.9956 | 0.9906 | 0.0337 | 0.9894 | 0.9918 |
|
| 150 |
+
| 0.0002 | 93.0 | 44826 | 0.9956 | 0.9906 | 0.0343 | 0.9897 | 0.9915 |
|
| 151 |
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| 0.0003 | 94.0 | 45308 | 0.9957 | 0.9910 | 0.0336 | 0.9901 | 0.9918 |
|
| 152 |
+
| 0.0002 | 95.0 | 45790 | 0.9954 | 0.9901 | 0.0355 | 0.9887 | 0.9915 |
|
| 153 |
+
| 0.0002 | 96.0 | 46272 | 0.9958 | 0.9904 | 0.0326 | 0.9894 | 0.9915 |
|
| 154 |
+
| 0.0002 | 97.0 | 46754 | 0.9959 | 0.9901 | 0.0334 | 0.9894 | 0.9908 |
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| 155 |
+
| 0.0002 | 98.0 | 47236 | 0.9959 | 0.9908 | 0.0337 | 0.9897 | 0.9918 |
|
| 156 |
+
| 0.0002 | 99.0 | 47718 | 0.9958 | 0.9908 | 0.0334 | 0.9897 | 0.9918 |
|
| 157 |
+
| 0.0002 | 100.0 | 48200 | 0.9957 | 0.9902 | 0.0347 | 0.9890 | 0.9915 |
|
| 158 |
+
| 0.0002 | 101.0 | 48682 | 0.9953 | 0.9894 | 0.0379 | 0.9873 | 0.9915 |
|
| 159 |
+
| 0.0002 | 102.0 | 49164 | 0.9957 | 0.9902 | 0.0340 | 0.9890 | 0.9915 |
|
| 160 |
+
| 0.0002 | 103.0 | 49646 | 0.9956 | 0.9894 | 0.0336 | 0.9890 | 0.9897 |
|
| 161 |
+
| 0.0001 | 104.0 | 50128 | 0.9954 | 0.9911 | 0.0362 | 0.9901 | 0.9922 |
|
| 162 |
+
| 0.0002 | 105.0 | 50610 | 0.9956 | 0.9902 | 0.0339 | 0.9890 | 0.9915 |
|
| 163 |
+
| 0.0002 | 106.0 | 51092 | 0.9957 | 0.9904 | 0.0339 | 0.9901 | 0.9908 |
|
| 164 |
+
| 0.0002 | 107.0 | 51574 | 0.9957 | 0.9897 | 0.0341 | 0.9900 | 0.9893 |
|
| 165 |
+
| 0.0002 | 108.0 | 52056 | 0.9955 | 0.9897 | 0.0350 | 0.9883 | 0.9911 |
|
| 166 |
+
| 0.0001 | 109.0 | 52538 | 0.9956 | 0.9910 | 0.0334 | 0.9901 | 0.9918 |
|
| 167 |
+
| 0.0001 | 110.0 | 53020 | 0.9954 | 0.9897 | 0.0364 | 0.9887 | 0.9908 |
|
| 168 |
+
| 0.0001 | 111.0 | 53502 | 0.9956 | 0.9886 | 0.0340 | 0.9879 | 0.9893 |
|
| 169 |
+
| 0.0001 | 112.0 | 53984 | 0.9955 | 0.9895 | 0.0346 | 0.9880 | 0.9911 |
|
| 170 |
+
| 0.0001 | 113.0 | 54466 | 0.9954 | 0.9897 | 0.0348 | 0.9887 | 0.9908 |
|
| 171 |
+
| 0.0001 | 114.0 | 54948 | 0.9956 | 0.9906 | 0.0347 | 0.9894 | 0.9918 |
|
| 172 |
+
| 0.0001 | 115.0 | 55430 | 0.9956 | 0.9899 | 0.0342 | 0.9890 | 0.9908 |
|
| 173 |
+
| 0.0001 | 116.0 | 55912 | 0.9957 | 0.9908 | 0.0344 | 0.9901 | 0.9915 |
|
| 174 |
+
| 0.0001 | 117.0 | 56394 | 0.9956 | 0.9895 | 0.0340 | 0.9887 | 0.9904 |
|
| 175 |
+
| 0.0001 | 118.0 | 56876 | 0.9955 | 0.9895 | 0.0347 | 0.9880 | 0.9911 |
|
| 176 |
+
| 0.0001 | 119.0 | 57358 | 0.9955 | 0.9901 | 0.0349 | 0.9887 | 0.9915 |
|
| 177 |
+
| 0.0001 | 120.0 | 57840 | 0.9955 | 0.9892 | 0.0351 | 0.9880 | 0.9904 |
|
| 178 |
+
| 0.0001 | 121.0 | 58322 | 0.9955 | 0.9899 | 0.0359 | 0.9883 | 0.9915 |
|
| 179 |
+
| 0.0001 | 122.0 | 58804 | 0.9955 | 0.9890 | 0.0365 | 0.9873 | 0.9908 |
|
| 180 |
+
| 0.0001 | 123.0 | 59286 | 0.9955 | 0.9883 | 0.0350 | 0.9869 | 0.9897 |
|
| 181 |
+
| 0.0001 | 124.0 | 59768 | 0.9955 | 0.9890 | 0.0344 | 0.9880 | 0.9901 |
|
| 182 |
+
| 0.0001 | 125.0 | 60250 | 0.9956 | 0.9890 | 0.0352 | 0.9897 | 0.9883 |
|
| 183 |
+
| 0.0001 | 126.0 | 60732 | 0.9953 | 0.9887 | 0.0359 | 0.9869 | 0.9904 |
|
| 184 |
+
| 0.0001 | 127.0 | 61214 | 0.9952 | 0.9876 | 0.0360 | 0.9862 | 0.9890 |
|
| 185 |
+
| 0.0001 | 128.0 | 61696 | 0.9953 | 0.9888 | 0.0357 | 0.9869 | 0.9908 |
|
| 186 |
+
| 0.0001 | 129.0 | 62178 | 0.9954 | 0.9888 | 0.0363 | 0.9869 | 0.9908 |
|
| 187 |
+
| 0.0001 | 130.0 | 62660 | 0.9954 | 0.9894 | 0.0360 | 0.9880 | 0.9908 |
|
| 188 |
+
| 0.0001 | 131.0 | 63142 | 0.9956 | 0.9890 | 0.0360 | 0.9883 | 0.9897 |
|
| 189 |
+
| 0.0001 | 132.0 | 63624 | 0.9954 | 0.9885 | 0.0362 | 0.9869 | 0.9901 |
|
| 190 |
+
| 0.0001 | 133.0 | 64106 | 0.9955 | 0.9888 | 0.0356 | 0.9876 | 0.9901 |
|
| 191 |
+
| 0.0001 | 134.0 | 64588 | 0.9954 | 0.9894 | 0.0367 | 0.9876 | 0.9911 |
|
| 192 |
+
| 0.0001 | 135.0 | 65070 | 0.9954 | 0.9894 | 0.0364 | 0.9876 | 0.9911 |
|
| 193 |
+
| 0.0001 | 136.0 | 65552 | 0.9954 | 0.9890 | 0.0363 | 0.9876 | 0.9904 |
|
| 194 |
+
| 0.0 | 137.0 | 66034 | 0.9954 | 0.9894 | 0.0369 | 0.9876 | 0.9911 |
|
| 195 |
+
| 0.0001 | 138.0 | 66516 | 0.9954 | 0.9894 | 0.0369 | 0.9876 | 0.9911 |
|
| 196 |
+
| 0.0001 | 139.0 | 66998 | 0.9956 | 0.9902 | 0.0358 | 0.9894 | 0.9911 |
|
| 197 |
+
| 0.0001 | 140.0 | 67480 | 0.9956 | 0.9901 | 0.0360 | 0.9887 | 0.9915 |
|
| 198 |
+
| 0.0001 | 141.0 | 67962 | 0.9957 | 0.9902 | 0.0357 | 0.9894 | 0.9911 |
|
| 199 |
+
| 0.0001 | 142.0 | 68444 | 0.9957 | 0.9902 | 0.0355 | 0.9894 | 0.9911 |
|
| 200 |
+
| 0.0001 | 143.0 | 68926 | 0.9957 | 0.9888 | 0.0349 | 0.9883 | 0.9893 |
|
| 201 |
+
| 0.0 | 144.0 | 69408 | 0.9956 | 0.9895 | 0.0357 | 0.9883 | 0.9908 |
|
| 202 |
+
| 0.0 | 145.0 | 69890 | 0.9955 | 0.9899 | 0.0361 | 0.9883 | 0.9915 |
|
| 203 |
+
| 0.0001 | 146.0 | 70372 | 0.9956 | 0.9902 | 0.0350 | 0.9894 | 0.9911 |
|
| 204 |
+
| 0.0001 | 147.0 | 70854 | 0.9956 | 0.9906 | 0.0354 | 0.9894 | 0.9918 |
|
| 205 |
+
| 0.0 | 148.0 | 71336 | 0.9956 | 0.9902 | 0.0351 | 0.9894 | 0.9911 |
|
| 206 |
+
| 0.0 | 149.0 | 71818 | 0.9956 | 0.9902 | 0.0352 | 0.9894 | 0.9911 |
|
| 207 |
+
| 0.0 | 150.0 | 72300 | 0.9956 | 0.9902 | 0.0352 | 0.9894 | 0.9911 |
|
| 208 |
|
| 209 |
|
| 210 |
### Framework versions
|
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 285162796
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:055f19cdcd7c0f43ae9cbc10a067ee12e7ca196f48a467d7dca0f44634de8996
|
| 3 |
size 285162796
|
training_args.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 5240
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:a2f9ecab04ba72d02b18c20b6fbeffd01f319c1051f7928e3c25981d561390f6
|
| 3 |
size 5240
|