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model_15M_medium_ds_masking_0.5_explicit_hs_predicted_hparamas

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  1. README.md +22 -28
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -16,8 +16,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0909
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- - Accuracy: 0.9693
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  ## Model description
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@@ -50,32 +50,26 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:------:|:-----:|:---------------:|:--------:|
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- | No log | 0 | 0 | 4.6167 | 0.0078 |
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- | 0.2687 | 0.2190 | 1953 | 0.2184 | 0.9291 |
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- | 0.1946 | 0.4379 | 3906 | 0.1820 | 0.9409 |
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- | 0.1794 | 0.6569 | 5859 | 0.1609 | 0.9474 |
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- | 0.1564 | 0.8759 | 7812 | 0.1466 | 0.9517 |
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- | 0.1459 | 1.0949 | 9765 | 0.1376 | 0.9546 |
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- | 0.1379 | 1.3138 | 11718 | 0.1296 | 0.9571 |
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- | 0.1315 | 1.5328 | 13671 | 0.1256 | 0.9584 |
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- | 0.1268 | 1.7518 | 15624 | 0.1228 | 0.9594 |
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- | 0.1229 | 1.9707 | 17577 | 0.1179 | 0.9609 |
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- | 0.1193 | 2.1897 | 19530 | 0.1143 | 0.9619 |
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- | 0.1181 | 2.4087 | 21483 | 0.1124 | 0.9625 |
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- | 0.1148 | 2.6276 | 23436 | 0.1090 | 0.9636 |
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- | 0.1124 | 2.8466 | 25389 | 0.1061 | 0.9644 |
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- | 0.1101 | 3.0656 | 27342 | 0.1041 | 0.9651 |
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- | 0.1083 | 3.2846 | 29295 | 0.1040 | 0.9652 |
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- | 0.106 | 3.5035 | 31248 | 0.1020 | 0.9658 |
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- | 0.1047 | 3.7225 | 33201 | 0.0996 | 0.9666 |
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- | 0.1024 | 3.9415 | 35154 | 0.0993 | 0.9666 |
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- | 0.1017 | 4.1604 | 37107 | 0.0967 | 0.9674 |
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- | 0.1013 | 4.3794 | 39060 | 0.0963 | 0.9674 |
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- | 0.0994 | 4.5984 | 41013 | 0.0948 | 0.9680 |
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- | 0.0975 | 4.8174 | 42966 | 0.0940 | 0.9683 |
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- | 0.0972 | 5.0363 | 44919 | 0.0928 | 0.9685 |
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- | 0.0964 | 5.2553 | 46872 | 0.0928 | 0.9686 |
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- | 0.0964 | 5.4743 | 48825 | 0.0918 | 0.9691 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0525
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+ - Accuracy: 0.9821
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:------:|:-----:|:---------------:|:--------:|
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+ | No log | 0 | 0 | 4.5649 | 0.0016 |
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+ | 0.1871 | 0.2190 | 1953 | 0.1446 | 0.9529 |
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+ | 0.1236 | 0.4379 | 3906 | 0.1085 | 0.9642 |
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+ | 0.1039 | 0.6569 | 5859 | 0.0930 | 0.9693 |
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+ | 0.0919 | 0.8759 | 7812 | 0.0838 | 0.9721 |
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+ | 0.1111 | 1.0949 | 9765 | 0.0806 | 0.9733 |
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+ | 0.0803 | 1.3138 | 11718 | 0.0749 | 0.9749 |
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+ | 0.0757 | 1.5328 | 13671 | 0.0719 | 0.9760 |
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+ | 0.0726 | 1.7518 | 15624 | 0.0689 | 0.9770 |
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+ | 0.0833 | 1.9707 | 17577 | 0.0701 | 0.9768 |
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+ | 0.0674 | 2.1897 | 19530 | 0.0639 | 0.9786 |
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+ | 0.0662 | 2.4087 | 21483 | 0.0616 | 0.9793 |
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+ | 0.0637 | 2.6276 | 23436 | 0.0596 | 0.9799 |
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+ | 0.0626 | 2.8466 | 25389 | 0.0576 | 0.9804 |
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+ | 0.0606 | 3.0656 | 27342 | 0.0564 | 0.9808 |
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+ | 0.0591 | 3.2846 | 29295 | 0.0561 | 0.9809 |
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+ | 0.0577 | 3.5035 | 31248 | 0.0541 | 0.9816 |
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+ | 0.0568 | 3.7225 | 33201 | 0.0531 | 0.9820 |
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+ | 0.0554 | 3.9415 | 35154 | 0.0531 | 0.9819 |
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+ | 0.0548 | 4.1604 | 37107 | 0.0522 | 0.9823 |
 
 
 
 
 
 
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  ### Framework versions
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training_args.bin CHANGED
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