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xlnet-base-cased-airlines-news-multi-label-8-actions

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  1. README.md +49 -49
  2. model.safetensors +2 -2
  3. runs/Jun06_22-59-57_ubuntu-System-Product-Name/events.out.tfevents.1717685998.ubuntu-System-Product-Name.460073.0 +3 -0
  4. runs/Jun06_23-22-13_ubuntu-System-Product-Name/events.out.tfevents.1717687334.ubuntu-System-Product-Name.460073.1 +3 -0
  5. runs/Jun06_23-22-13_ubuntu-System-Product-Name/events.out.tfevents.1717690811.ubuntu-System-Product-Name.460073.2 +3 -0
  6. training_args.bin +1 -1
README.md CHANGED
@@ -17,9 +17,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [xlnet/xlnet-base-cased](https://huggingface.co/xlnet/xlnet-base-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2041
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- - F1: 0.9254
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- - Jaccard: 0.6493
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  ## Model description
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@@ -38,7 +38,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 9e-05
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  - train_batch_size: 32
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  - eval_batch_size: 32
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  - seed: 42
@@ -51,51 +51,51 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | F1 | Jaccard |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
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- | No log | 1.0 | 57 | 0.4153 | 0.8352 | 0.3850 |
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- | No log | 2.0 | 114 | 0.3085 | 0.8357 | 0.3850 |
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- | No log | 3.0 | 171 | 0.2791 | 0.8685 | 0.3982 |
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- | No log | 4.0 | 228 | 0.2607 | 0.8726 | 0.4550 |
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- | No log | 5.0 | 285 | 0.2476 | 0.8898 | 0.4971 |
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- | No log | 6.0 | 342 | 0.2372 | 0.8933 | 0.5184 |
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- | No log | 7.0 | 399 | 0.2296 | 0.8986 | 0.5645 |
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- | No log | 8.0 | 456 | 0.2260 | 0.9049 | 0.5690 |
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- | 0.3101 | 9.0 | 513 | 0.2234 | 0.9047 | 0.5715 |
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- | 0.3101 | 10.0 | 570 | 0.2171 | 0.9149 | 0.6058 |
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- | 0.3101 | 11.0 | 627 | 0.2152 | 0.9123 | 0.5970 |
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- | 0.3101 | 12.0 | 684 | 0.2122 | 0.9141 | 0.6014 |
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- | 0.3101 | 13.0 | 741 | 0.2100 | 0.9197 | 0.6239 |
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- | 0.3101 | 14.0 | 798 | 0.2096 | 0.9163 | 0.6169 |
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- | 0.3101 | 15.0 | 855 | 0.2097 | 0.9202 | 0.6412 |
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- | 0.3101 | 16.0 | 912 | 0.2067 | 0.9231 | 0.6405 |
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- | 0.3101 | 17.0 | 969 | 0.2046 | 0.9230 | 0.6368 |
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- | 0.2256 | 18.0 | 1026 | 0.2040 | 0.9241 | 0.6486 |
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- | 0.2256 | 19.0 | 1083 | 0.2031 | 0.9253 | 0.6449 |
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- | 0.2256 | 20.0 | 1140 | 0.2022 | 0.9227 | 0.6515 |
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- | 0.2256 | 21.0 | 1197 | 0.2041 | 0.9240 | 0.6493 |
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- | 0.2256 | 22.0 | 1254 | 0.2041 | 0.9254 | 0.6493 |
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- | 0.2256 | 23.0 | 1311 | 0.2013 | 0.9210 | 0.6471 |
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- | 0.2256 | 24.0 | 1368 | 0.2013 | 0.9234 | 0.6515 |
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- | 0.2256 | 25.0 | 1425 | 0.2015 | 0.9234 | 0.6397 |
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- | 0.2256 | 26.0 | 1482 | 0.1999 | 0.9235 | 0.6574 |
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- | 0.2117 | 27.0 | 1539 | 0.2000 | 0.9237 | 0.6523 |
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- | 0.2117 | 28.0 | 1596 | 0.1998 | 0.9239 | 0.6361 |
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- | 0.2117 | 29.0 | 1653 | 0.1987 | 0.9211 | 0.6442 |
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- | 0.2117 | 30.0 | 1710 | 0.1988 | 0.9230 | 0.6530 |
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- | 0.2117 | 31.0 | 1767 | 0.1997 | 0.9235 | 0.6589 |
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- | 0.2117 | 32.0 | 1824 | 0.1995 | 0.9228 | 0.6582 |
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- | 0.2117 | 33.0 | 1881 | 0.1982 | 0.9197 | 0.6434 |
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- | 0.2117 | 34.0 | 1938 | 0.1983 | 0.9209 | 0.6508 |
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- | 0.2117 | 35.0 | 1995 | 0.1985 | 0.9217 | 0.6538 |
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- | 0.2057 | 36.0 | 2052 | 0.1993 | 0.9247 | 0.6597 |
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- | 0.2057 | 37.0 | 2109 | 0.1981 | 0.9217 | 0.6538 |
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- | 0.2057 | 38.0 | 2166 | 0.1977 | 0.9238 | 0.6597 |
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- | 0.2057 | 39.0 | 2223 | 0.1974 | 0.9229 | 0.6560 |
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- | 0.2057 | 40.0 | 2280 | 0.1978 | 0.9223 | 0.6538 |
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- | 0.2057 | 41.0 | 2337 | 0.1976 | 0.9217 | 0.6538 |
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- | 0.2057 | 42.0 | 2394 | 0.1976 | 0.9229 | 0.6552 |
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- | 0.2057 | 43.0 | 2451 | 0.1975 | 0.9229 | 0.6552 |
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- | 0.2023 | 44.0 | 2508 | 0.1975 | 0.9229 | 0.6552 |
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- | 0.2023 | 45.0 | 2565 | 0.1975 | 0.9223 | 0.6538 |
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  ### Framework versions
 
17
 
18
  This model is a fine-tuned version of [xlnet/xlnet-base-cased](https://huggingface.co/xlnet/xlnet-base-cased) on the None dataset.
19
  It achieves the following results on the evaluation set:
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+ - Loss: 0.1864
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+ - F1: 0.9349
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+ - Jaccard: 0.6652
23
 
24
  ## Model description
25
 
 
38
  ### Training hyperparameters
39
 
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  The following hyperparameters were used during training:
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+ - learning_rate: 0.0001
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  - train_batch_size: 32
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  - eval_batch_size: 32
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | F1 | Jaccard |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
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+ | No log | 1.0 | 57 | 0.3740 | 0.8583 | 0.4115 |
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+ | No log | 2.0 | 114 | 0.2826 | 0.8583 | 0.4115 |
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+ | No log | 3.0 | 171 | 0.2538 | 0.8890 | 0.4558 |
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+ | No log | 4.0 | 228 | 0.2369 | 0.8936 | 0.5007 |
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+ | No log | 5.0 | 285 | 0.2252 | 0.9036 | 0.5236 |
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+ | No log | 6.0 | 342 | 0.2181 | 0.9070 | 0.5450 |
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+ | No log | 7.0 | 399 | 0.2147 | 0.9168 | 0.5793 |
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+ | No log | 8.0 | 456 | 0.2105 | 0.9172 | 0.5653 |
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+ | 0.3052 | 9.0 | 513 | 0.2058 | 0.9199 | 0.5874 |
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+ | 0.3052 | 10.0 | 570 | 0.2046 | 0.9204 | 0.6040 |
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+ | 0.3052 | 11.0 | 627 | 0.2018 | 0.9214 | 0.5962 |
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+ | 0.3052 | 12.0 | 684 | 0.1990 | 0.9242 | 0.6132 |
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+ | 0.3052 | 13.0 | 741 | 0.1987 | 0.9223 | 0.6103 |
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+ | 0.3052 | 14.0 | 798 | 0.1974 | 0.9235 | 0.6191 |
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+ | 0.3052 | 15.0 | 855 | 0.1962 | 0.9213 | 0.6169 |
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+ | 0.3052 | 16.0 | 912 | 0.1958 | 0.9255 | 0.6235 |
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+ | 0.3052 | 17.0 | 969 | 0.1932 | 0.9264 | 0.6176 |
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+ | 0.2221 | 18.0 | 1026 | 0.1927 | 0.9276 | 0.6423 |
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+ | 0.2221 | 19.0 | 1083 | 0.1926 | 0.9279 | 0.6338 |
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+ | 0.2221 | 20.0 | 1140 | 0.1910 | 0.9288 | 0.6434 |
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+ | 0.2221 | 21.0 | 1197 | 0.1924 | 0.9271 | 0.6316 |
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+ | 0.2221 | 22.0 | 1254 | 0.1904 | 0.9285 | 0.6353 |
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+ | 0.2221 | 23.0 | 1311 | 0.1883 | 0.9288 | 0.6475 |
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+ | 0.2221 | 24.0 | 1368 | 0.1877 | 0.9302 | 0.6504 |
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+ | 0.2221 | 25.0 | 1425 | 0.1890 | 0.9291 | 0.6442 |
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+ | 0.2221 | 26.0 | 1482 | 0.1878 | 0.9318 | 0.6659 |
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+ | 0.2088 | 27.0 | 1539 | 0.1882 | 0.9308 | 0.6593 |
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+ | 0.2088 | 28.0 | 1596 | 0.1867 | 0.9347 | 0.6597 |
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+ | 0.2088 | 29.0 | 1653 | 0.1864 | 0.9349 | 0.6652 |
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+ | 0.2088 | 30.0 | 1710 | 0.1866 | 0.9345 | 0.6681 |
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+ | 0.2088 | 31.0 | 1767 | 0.1871 | 0.9341 | 0.6670 |
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+ | 0.2088 | 32.0 | 1824 | 0.1862 | 0.9324 | 0.6622 |
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+ | 0.2088 | 33.0 | 1881 | 0.1878 | 0.9325 | 0.6589 |
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+ | 0.2088 | 34.0 | 1938 | 0.1866 | 0.9332 | 0.6633 |
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+ | 0.2088 | 35.0 | 1995 | 0.1858 | 0.9330 | 0.6674 |
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+ | 0.2021 | 36.0 | 2052 | 0.1863 | 0.9298 | 0.6479 |
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+ | 0.2021 | 37.0 | 2109 | 0.1858 | 0.9325 | 0.6630 |
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+ | 0.2021 | 38.0 | 2166 | 0.1861 | 0.9320 | 0.6652 |
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+ | 0.2021 | 39.0 | 2223 | 0.1854 | 0.9325 | 0.6652 |
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+ | 0.2021 | 40.0 | 2280 | 0.1852 | 0.9330 | 0.6674 |
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+ | 0.2021 | 41.0 | 2337 | 0.1856 | 0.9318 | 0.6608 |
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+ | 0.2021 | 42.0 | 2394 | 0.1857 | 0.9318 | 0.6608 |
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+ | 0.2021 | 43.0 | 2451 | 0.1856 | 0.9324 | 0.6652 |
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+ | 0.198 | 44.0 | 2508 | 0.1855 | 0.9325 | 0.6652 |
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+ | 0.198 | 45.0 | 2565 | 0.1855 | 0.9325 | 0.6652 |
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  ### Framework versions
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