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---
license: mit
base_model: xlnet/xlnet-base-cased
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: xlnet-base-cased-airlines-news-multi-label-8-actions
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# xlnet-base-cased-airlines-news-multi-label-8-actions
This model is a fine-tuned version of [xlnet/xlnet-base-cased](https://huggingface.co./xlnet/xlnet-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1864
- F1: 0.9349
- Jaccard: 0.6652
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 150
- num_epochs: 45
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Jaccard |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
| No log | 1.0 | 57 | 0.3740 | 0.8583 | 0.4115 |
| No log | 2.0 | 114 | 0.2826 | 0.8583 | 0.4115 |
| No log | 3.0 | 171 | 0.2538 | 0.8890 | 0.4558 |
| No log | 4.0 | 228 | 0.2369 | 0.8936 | 0.5007 |
| No log | 5.0 | 285 | 0.2252 | 0.9036 | 0.5236 |
| No log | 6.0 | 342 | 0.2181 | 0.9070 | 0.5450 |
| No log | 7.0 | 399 | 0.2147 | 0.9168 | 0.5793 |
| No log | 8.0 | 456 | 0.2105 | 0.9172 | 0.5653 |
| 0.3052 | 9.0 | 513 | 0.2058 | 0.9199 | 0.5874 |
| 0.3052 | 10.0 | 570 | 0.2046 | 0.9204 | 0.6040 |
| 0.3052 | 11.0 | 627 | 0.2018 | 0.9214 | 0.5962 |
| 0.3052 | 12.0 | 684 | 0.1990 | 0.9242 | 0.6132 |
| 0.3052 | 13.0 | 741 | 0.1987 | 0.9223 | 0.6103 |
| 0.3052 | 14.0 | 798 | 0.1974 | 0.9235 | 0.6191 |
| 0.3052 | 15.0 | 855 | 0.1962 | 0.9213 | 0.6169 |
| 0.3052 | 16.0 | 912 | 0.1958 | 0.9255 | 0.6235 |
| 0.3052 | 17.0 | 969 | 0.1932 | 0.9264 | 0.6176 |
| 0.2221 | 18.0 | 1026 | 0.1927 | 0.9276 | 0.6423 |
| 0.2221 | 19.0 | 1083 | 0.1926 | 0.9279 | 0.6338 |
| 0.2221 | 20.0 | 1140 | 0.1910 | 0.9288 | 0.6434 |
| 0.2221 | 21.0 | 1197 | 0.1924 | 0.9271 | 0.6316 |
| 0.2221 | 22.0 | 1254 | 0.1904 | 0.9285 | 0.6353 |
| 0.2221 | 23.0 | 1311 | 0.1883 | 0.9288 | 0.6475 |
| 0.2221 | 24.0 | 1368 | 0.1877 | 0.9302 | 0.6504 |
| 0.2221 | 25.0 | 1425 | 0.1890 | 0.9291 | 0.6442 |
| 0.2221 | 26.0 | 1482 | 0.1878 | 0.9318 | 0.6659 |
| 0.2088 | 27.0 | 1539 | 0.1882 | 0.9308 | 0.6593 |
| 0.2088 | 28.0 | 1596 | 0.1867 | 0.9347 | 0.6597 |
| 0.2088 | 29.0 | 1653 | 0.1864 | 0.9349 | 0.6652 |
| 0.2088 | 30.0 | 1710 | 0.1866 | 0.9345 | 0.6681 |
| 0.2088 | 31.0 | 1767 | 0.1871 | 0.9341 | 0.6670 |
| 0.2088 | 32.0 | 1824 | 0.1862 | 0.9324 | 0.6622 |
| 0.2088 | 33.0 | 1881 | 0.1878 | 0.9325 | 0.6589 |
| 0.2088 | 34.0 | 1938 | 0.1866 | 0.9332 | 0.6633 |
| 0.2088 | 35.0 | 1995 | 0.1858 | 0.9330 | 0.6674 |
| 0.2021 | 36.0 | 2052 | 0.1863 | 0.9298 | 0.6479 |
| 0.2021 | 37.0 | 2109 | 0.1858 | 0.9325 | 0.6630 |
| 0.2021 | 38.0 | 2166 | 0.1861 | 0.9320 | 0.6652 |
| 0.2021 | 39.0 | 2223 | 0.1854 | 0.9325 | 0.6652 |
| 0.2021 | 40.0 | 2280 | 0.1852 | 0.9330 | 0.6674 |
| 0.2021 | 41.0 | 2337 | 0.1856 | 0.9318 | 0.6608 |
| 0.2021 | 42.0 | 2394 | 0.1857 | 0.9318 | 0.6608 |
| 0.2021 | 43.0 | 2451 | 0.1856 | 0.9324 | 0.6652 |
| 0.198 | 44.0 | 2508 | 0.1855 | 0.9325 | 0.6652 |
| 0.198 | 45.0 | 2565 | 0.1855 | 0.9325 | 0.6652 |
### Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1