---
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: 0.2567
- F1: 0.8989
- Roc Auc: 0.6475

## 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: 7e-05
- train_batch_size: 12
- eval_batch_size: 12
- 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: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
| No log        | 1.0   | 170  | 0.2834          | 0.8827 | 0.5576  |
| No log        | 2.0   | 340  | 0.2670          | 0.8918 | 0.6102  |
| 0.2923        | 3.0   | 510  | 0.2567          | 0.8989 | 0.6475  |
| 0.2923        | 4.0   | 680  | 0.2526          | 0.8910 | 0.6685  |
| 0.2923        | 5.0   | 850  | 0.2512          | 0.8825 | 0.6352  |
| 0.2571        | 6.0   | 1020 | 0.2514          | 0.8863 | 0.6708  |
| 0.2571        | 7.0   | 1190 | 0.2454          | 0.8872 | 0.6490  |
| 0.2571        | 8.0   | 1360 | 0.2495          | 0.8884 | 0.6660  |
| 0.2468        | 9.0   | 1530 | 0.2467          | 0.8881 | 0.6725  |
| 0.2468        | 10.0  | 1700 | 0.2554          | 0.8815 | 0.6514  |
| 0.2468        | 11.0  | 1870 | 0.2474          | 0.8883 | 0.6603  |
| 0.2363        | 12.0  | 2040 | 0.2478          | 0.8912 | 0.6943  |
| 0.2363        | 13.0  | 2210 | 0.2492          | 0.8964 | 0.6976  |
| 0.2363        | 14.0  | 2380 | 0.2530          | 0.8936 | 0.7121  |
| 0.2332        | 15.0  | 2550 | 0.2497          | 0.8893 | 0.6830  |
| 0.2332        | 16.0  | 2720 | 0.2483          | 0.8922 | 0.7008  |
| 0.2332        | 17.0  | 2890 | 0.2489          | 0.8905 | 0.6782  |
| 0.23          | 18.0  | 3060 | 0.2496          | 0.8877 | 0.6927  |
| 0.23          | 19.0  | 3230 | 0.2494          | 0.8855 | 0.6652  |
| 0.23          | 20.0  | 3400 | 0.2483          | 0.8929 | 0.6903  |
| 0.2246        | 21.0  | 3570 | 0.2503          | 0.8902 | 0.6838  |
| 0.2246        | 22.0  | 3740 | 0.2506          | 0.8854 | 0.6805  |
| 0.2246        | 23.0  | 3910 | 0.2515          | 0.8900 | 0.6887  |
| 0.2214        | 24.0  | 4080 | 0.2501          | 0.8894 | 0.6773  |
| 0.2214        | 25.0  | 4250 | 0.2528          | 0.8878 | 0.6870  |
| 0.2214        | 26.0  | 4420 | 0.2519          | 0.8918 | 0.6895  |
| 0.2203        | 27.0  | 4590 | 0.2558          | 0.8897 | 0.6830  |
| 0.2203        | 28.0  | 4760 | 0.2554          | 0.8919 | 0.6952  |
| 0.2203        | 29.0  | 4930 | 0.2537          | 0.8957 | 0.7025  |
| 0.2193        | 30.0  | 5100 | 0.2513          | 0.8951 | 0.7025  |
| 0.2193        | 31.0  | 5270 | 0.2565          | 0.8946 | 0.7130  |
| 0.2193        | 32.0  | 5440 | 0.2542          | 0.8935 | 0.6960  |
| 0.2178        | 33.0  | 5610 | 0.2545          | 0.8970 | 0.7090  |
| 0.2178        | 34.0  | 5780 | 0.2546          | 0.8960 | 0.7138  |
| 0.2178        | 35.0  | 5950 | 0.2550          | 0.8942 | 0.7073  |
| 0.2173        | 36.0  | 6120 | 0.2545          | 0.8942 | 0.7073  |
| 0.2173        | 37.0  | 6290 | 0.2537          | 0.8925 | 0.7008  |
| 0.2173        | 38.0  | 6460 | 0.2541          | 0.8942 | 0.7073  |
| 0.2164        | 39.0  | 6630 | 0.2537          | 0.8940 | 0.7016  |
| 0.2164        | 40.0  | 6800 | 0.2540          | 0.8942 | 0.7073  |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1