---
license: mit
base_model: xlnet/xlnet-base-cased
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: xlnet-base-cased-airlines-news-multi-label
  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

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: 0.2250
- F1: 0.9209
- Jaccard: 0.6829

## 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: 9e-05
- 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: 65

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Jaccard |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
| No log        | 1.0   | 57   | 0.3815          | 0.8283 | 0.4558  |
| No log        | 2.0   | 114  | 0.3186          | 0.8287 | 0.4602  |
| No log        | 3.0   | 171  | 0.2839          | 0.8781 | 0.5133  |
| No log        | 4.0   | 228  | 0.2660          | 0.8890 | 0.5457  |
| No log        | 5.0   | 285  | 0.2532          | 0.8996 | 0.5833  |
| No log        | 6.0   | 342  | 0.2471          | 0.8966 | 0.5745  |
| No log        | 7.0   | 399  | 0.2412          | 0.9066 | 0.6069  |
| No log        | 8.0   | 456  | 0.2393          | 0.9065 | 0.5981  |
| 0.323         | 9.0   | 513  | 0.2354          | 0.9043 | 0.6025  |
| 0.323         | 10.0  | 570  | 0.2340          | 0.9087 | 0.6077  |
| 0.323         | 11.0  | 627  | 0.2326          | 0.9122 | 0.6283  |
| 0.323         | 12.0  | 684  | 0.2305          | 0.9161 | 0.6401  |
| 0.323         | 13.0  | 741  | 0.2297          | 0.9113 | 0.6350  |
| 0.323         | 14.0  | 798  | 0.2284          | 0.9138 | 0.6416  |
| 0.323         | 15.0  | 855  | 0.2281          | 0.9130 | 0.6497  |
| 0.323         | 16.0  | 912  | 0.2248          | 0.9164 | 0.6527  |
| 0.323         | 17.0  | 969  | 0.2228          | 0.9166 | 0.6527  |
| 0.2463        | 18.0  | 1026 | 0.2232          | 0.9169 | 0.6586  |
| 0.2463        | 19.0  | 1083 | 0.2243          | 0.9162 | 0.6571  |
| 0.2463        | 20.0  | 1140 | 0.2236          | 0.9147 | 0.6519  |
| 0.2463        | 21.0  | 1197 | 0.2255          | 0.9203 | 0.6637  |
| 0.2463        | 22.0  | 1254 | 0.2261          | 0.9177 | 0.6556  |
| 0.2463        | 23.0  | 1311 | 0.2226          | 0.9169 | 0.6637  |
| 0.2463        | 24.0  | 1368 | 0.2226          | 0.9175 | 0.6718  |
| 0.2463        | 25.0  | 1425 | 0.2246          | 0.9147 | 0.6571  |
| 0.2463        | 26.0  | 1482 | 0.2240          | 0.9147 | 0.6637  |
| 0.2313        | 27.0  | 1539 | 0.2237          | 0.9164 | 0.6622  |
| 0.2313        | 28.0  | 1596 | 0.2235          | 0.9176 | 0.6711  |
| 0.2313        | 29.0  | 1653 | 0.2228          | 0.9154 | 0.6689  |
| 0.2313        | 30.0  | 1710 | 0.2220          | 0.9165 | 0.6748  |
| 0.2313        | 31.0  | 1767 | 0.2231          | 0.9168 | 0.6696  |
| 0.2313        | 32.0  | 1824 | 0.2231          | 0.9176 | 0.6718  |
| 0.2313        | 33.0  | 1881 | 0.2241          | 0.9166 | 0.6704  |
| 0.2313        | 34.0  | 1938 | 0.2224          | 0.9167 | 0.6704  |
| 0.2313        | 35.0  | 1995 | 0.2219          | 0.9168 | 0.6748  |
| 0.2248        | 36.0  | 2052 | 0.2250          | 0.9209 | 0.6829  |
| 0.2248        | 37.0  | 2109 | 0.2235          | 0.9139 | 0.6593  |
| 0.2248        | 38.0  | 2166 | 0.2226          | 0.9146 | 0.6659  |
| 0.2248        | 39.0  | 2223 | 0.2228          | 0.9176 | 0.6748  |
| 0.2248        | 40.0  | 2280 | 0.2227          | 0.9152 | 0.6637  |
| 0.2248        | 41.0  | 2337 | 0.2225          | 0.9151 | 0.6652  |
| 0.2248        | 42.0  | 2394 | 0.2224          | 0.9134 | 0.6593  |
| 0.2248        | 43.0  | 2451 | 0.2225          | 0.9175 | 0.6748  |
| 0.2201        | 44.0  | 2508 | 0.2219          | 0.9158 | 0.6637  |
| 0.2201        | 45.0  | 2565 | 0.2222          | 0.9151 | 0.6659  |
| 0.2201        | 46.0  | 2622 | 0.2211          | 0.9160 | 0.6681  |
| 0.2201        | 47.0  | 2679 | 0.2214          | 0.9167 | 0.6696  |
| 0.2201        | 48.0  | 2736 | 0.2218          | 0.9163 | 0.6681  |
| 0.2201        | 49.0  | 2793 | 0.2217          | 0.9146 | 0.6615  |
| 0.2201        | 50.0  | 2850 | 0.2216          | 0.9135 | 0.6593  |
| 0.2201        | 51.0  | 2907 | 0.2217          | 0.9174 | 0.6770  |
| 0.2201        | 52.0  | 2964 | 0.2219          | 0.9166 | 0.6755  |
| 0.2162        | 53.0  | 3021 | 0.2219          | 0.9165 | 0.6748  |
| 0.2162        | 54.0  | 3078 | 0.2214          | 0.9182 | 0.6814  |
| 0.2162        | 55.0  | 3135 | 0.2211          | 0.9165 | 0.6792  |
| 0.2162        | 56.0  | 3192 | 0.2211          | 0.9169 | 0.6748  |
| 0.2162        | 57.0  | 3249 | 0.2211          | 0.9149 | 0.6726  |
| 0.2162        | 58.0  | 3306 | 0.2209          | 0.9167 | 0.6814  |
| 0.2162        | 59.0  | 3363 | 0.2213          | 0.9167 | 0.6726  |
| 0.2162        | 60.0  | 3420 | 0.2215          | 0.9158 | 0.6726  |
| 0.2162        | 61.0  | 3477 | 0.2211          | 0.9150 | 0.6681  |
| 0.2157        | 62.0  | 3534 | 0.2211          | 0.9166 | 0.6748  |
| 0.2157        | 63.0  | 3591 | 0.2209          | 0.9157 | 0.6770  |
| 0.2157        | 64.0  | 3648 | 0.2209          | 0.9165 | 0.6748  |
| 0.2157        | 65.0  | 3705 | 0.2209          | 0.9157 | 0.6726  |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1