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distilbert-base-uncased_fold_10_binary_v1

Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
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update model card README.md

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@@ -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 [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.6148
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- - F1: 0.8251
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  ## Model description
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@@ -48,31 +48,31 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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- | No log | 1.0 | 289 | 0.3844 | 0.8200 |
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- | 0.403 | 2.0 | 578 | 0.3623 | 0.8264 |
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- | 0.403 | 3.0 | 867 | 0.4996 | 0.8258 |
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- | 0.203 | 4.0 | 1156 | 0.6593 | 0.8263 |
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- | 0.203 | 5.0 | 1445 | 0.7758 | 0.8242 |
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- | 0.0884 | 6.0 | 1734 | 0.9154 | 0.8071 |
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- | 0.0366 | 7.0 | 2023 | 1.0036 | 0.8232 |
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- | 0.0366 | 8.0 | 2312 | 1.0530 | 0.8390 |
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- | 0.0181 | 9.0 | 2601 | 1.2204 | 0.8260 |
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- | 0.0181 | 10.0 | 2890 | 1.2125 | 0.8247 |
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- | 0.008 | 11.0 | 3179 | 1.3317 | 0.8147 |
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- | 0.008 | 12.0 | 3468 | 1.3047 | 0.8240 |
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- | 0.0086 | 13.0 | 3757 | 1.4167 | 0.8204 |
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- | 0.007 | 14.0 | 4046 | 1.4070 | 0.8225 |
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- | 0.007 | 15.0 | 4335 | 1.4840 | 0.8178 |
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- | 0.0032 | 16.0 | 4624 | 1.4958 | 0.8158 |
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- | 0.0032 | 17.0 | 4913 | 1.5192 | 0.8201 |
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- | 0.0039 | 18.0 | 5202 | 1.5993 | 0.8094 |
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- | 0.0039 | 19.0 | 5491 | 1.5191 | 0.8225 |
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- | 0.0044 | 20.0 | 5780 | 1.5418 | 0.8231 |
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- | 0.0004 | 21.0 | 6069 | 1.5481 | 0.8263 |
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- | 0.0004 | 22.0 | 6358 | 1.5461 | 0.8342 |
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- | 0.0002 | 23.0 | 6647 | 1.5694 | 0.8268 |
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- | 0.0002 | 24.0 | 6936 | 1.5997 | 0.8271 |
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- | 0.0001 | 25.0 | 7225 | 1.6148 | 0.8251 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.6912
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+ - F1: 0.7977
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | No log | 1.0 | 288 | 0.4002 | 0.8012 |
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+ | 0.4056 | 2.0 | 576 | 0.4372 | 0.8075 |
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+ | 0.4056 | 3.0 | 864 | 0.4720 | 0.8071 |
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+ | 0.1958 | 4.0 | 1152 | 0.8156 | 0.7980 |
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+ | 0.1958 | 5.0 | 1440 | 0.8633 | 0.8055 |
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+ | 0.0847 | 6.0 | 1728 | 0.9761 | 0.8041 |
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+ | 0.0356 | 7.0 | 2016 | 1.1816 | 0.7861 |
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+ | 0.0356 | 8.0 | 2304 | 1.2251 | 0.7918 |
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+ | 0.0215 | 9.0 | 2592 | 1.3423 | 0.7798 |
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+ | 0.0215 | 10.0 | 2880 | 1.3888 | 0.7913 |
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+ | 0.013 | 11.0 | 3168 | 1.2899 | 0.8040 |
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+ | 0.013 | 12.0 | 3456 | 1.4247 | 0.8051 |
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+ | 0.0049 | 13.0 | 3744 | 1.5436 | 0.7991 |
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+ | 0.0061 | 14.0 | 4032 | 1.5762 | 0.7991 |
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+ | 0.0061 | 15.0 | 4320 | 1.5461 | 0.7998 |
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+ | 0.0054 | 16.0 | 4608 | 1.5622 | 0.8018 |
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+ | 0.0054 | 17.0 | 4896 | 1.6658 | 0.7991 |
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+ | 0.0021 | 18.0 | 5184 | 1.6765 | 0.7972 |
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+ | 0.0021 | 19.0 | 5472 | 1.6864 | 0.7973 |
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+ | 0.0052 | 20.0 | 5760 | 1.6303 | 0.8030 |
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+ | 0.0029 | 21.0 | 6048 | 1.6631 | 0.7947 |
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+ | 0.0029 | 22.0 | 6336 | 1.6571 | 0.8006 |
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+ | 0.0027 | 23.0 | 6624 | 1.6729 | 0.7949 |
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+ | 0.0027 | 24.0 | 6912 | 1.6931 | 0.7934 |
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+ | 0.0001 | 25.0 | 7200 | 1.6912 | 0.7977 |
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  ### Framework versions