---
base_model: microsoft/mpnet-base
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: mpnet-base-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. -->

# mpnet-base-airlines-news-multi-label

This model is a fine-tuned version of [microsoft/mpnet-base](https://huggingface.co/microsoft/mpnet-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2601
- F1: 0.8921
- Roc Auc: 0.6253

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 65

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
| No log        | 1.0   | 57   | 0.3852          | 0.8161 | 0.5     |
| No log        | 2.0   | 114  | 0.3612          | 0.8161 | 0.5     |
| No log        | 3.0   | 171  | 0.3569          | 0.8161 | 0.5     |
| No log        | 4.0   | 228  | 0.3515          | 0.8161 | 0.5     |
| No log        | 5.0   | 285  | 0.3453          | 0.8161 | 0.5     |
| No log        | 6.0   | 342  | 0.3403          | 0.8161 | 0.5     |
| No log        | 7.0   | 399  | 0.3345          | 0.8161 | 0.5     |
| No log        | 8.0   | 456  | 0.3292          | 0.8161 | 0.5     |
| 0.3585        | 9.0   | 513  | 0.3252          | 0.8161 | 0.5     |
| 0.3585        | 10.0  | 570  | 0.3175          | 0.8161 | 0.5     |
| 0.3585        | 11.0  | 627  | 0.3129          | 0.8161 | 0.5     |
| 0.3585        | 12.0  | 684  | 0.3076          | 0.8351 | 0.5029  |
| 0.3585        | 13.0  | 741  | 0.3024          | 0.8425 | 0.5109  |
| 0.3585        | 14.0  | 798  | 0.2995          | 0.8516 | 0.5163  |
| 0.3585        | 15.0  | 855  | 0.2953          | 0.8528 | 0.5221  |
| 0.3585        | 16.0  | 912  | 0.2904          | 0.8744 | 0.5426  |
| 0.3585        | 17.0  | 969  | 0.2875          | 0.8738 | 0.5451  |
| 0.2943        | 18.0  | 1026 | 0.2835          | 0.8833 | 0.5798  |
| 0.2943        | 19.0  | 1083 | 0.2811          | 0.8799 | 0.5710  |
| 0.2943        | 20.0  | 1140 | 0.2786          | 0.8815 | 0.5873  |
| 0.2943        | 21.0  | 1197 | 0.2761          | 0.8815 | 0.5873  |
| 0.2943        | 22.0  | 1254 | 0.2750          | 0.8838 | 0.5906  |
| 0.2943        | 23.0  | 1311 | 0.2705          | 0.8905 | 0.6194  |
| 0.2943        | 24.0  | 1368 | 0.2687          | 0.8911 | 0.6224  |
| 0.2943        | 25.0  | 1425 | 0.2674          | 0.8895 | 0.6165  |
| 0.2943        | 26.0  | 1482 | 0.2652          | 0.8911 | 0.6224  |
| 0.2666        | 27.0  | 1539 | 0.2642          | 0.8911 | 0.6224  |
| 0.2666        | 28.0  | 1596 | 0.2634          | 0.8903 | 0.6194  |
| 0.2666        | 29.0  | 1653 | 0.2612          | 0.8903 | 0.6194  |
| 0.2666        | 30.0  | 1710 | 0.2601          | 0.8921 | 0.6253  |
| 0.2666        | 31.0  | 1767 | 0.2583          | 0.8913 | 0.6328  |
| 0.2666        | 32.0  | 1824 | 0.2568          | 0.8864 | 0.6319  |
| 0.2666        | 33.0  | 1881 | 0.2563          | 0.8861 | 0.6319  |
| 0.2666        | 34.0  | 1938 | 0.2552          | 0.8869 | 0.6349  |
| 0.2666        | 35.0  | 1995 | 0.2544          | 0.8884 | 0.6378  |
| 0.2516        | 36.0  | 2052 | 0.2530          | 0.8875 | 0.6374  |
| 0.2516        | 37.0  | 2109 | 0.2523          | 0.8876 | 0.6374  |
| 0.2516        | 38.0  | 2166 | 0.2514          | 0.8889 | 0.6432  |
| 0.2516        | 39.0  | 2223 | 0.2504          | 0.8874 | 0.6453  |
| 0.2516        | 40.0  | 2280 | 0.2502          | 0.8892 | 0.6432  |
| 0.2516        | 41.0  | 2337 | 0.2495          | 0.8862 | 0.6419  |
| 0.2516        | 42.0  | 2394 | 0.2490          | 0.8867 | 0.6445  |
| 0.2516        | 43.0  | 2451 | 0.2491          | 0.8859 | 0.6365  |
| 0.2442        | 44.0  | 2508 | 0.2480          | 0.8906 | 0.6511  |
| 0.2442        | 45.0  | 2565 | 0.2476          | 0.8894 | 0.6457  |
| 0.2442        | 46.0  | 2622 | 0.2476          | 0.8888 | 0.6478  |
| 0.2442        | 47.0  | 2679 | 0.2474          | 0.8906 | 0.6511  |
| 0.2442        | 48.0  | 2736 | 0.2462          | 0.8890 | 0.6507  |
| 0.2442        | 49.0  | 2793 | 0.2461          | 0.8920 | 0.6545  |
| 0.2442        | 50.0  | 2850 | 0.2455          | 0.8894 | 0.6532  |
| 0.2442        | 51.0  | 2907 | 0.2457          | 0.8897 | 0.6507  |
| 0.2442        | 52.0  | 2964 | 0.2452          | 0.8894 | 0.6532  |
| 0.238         | 53.0  | 3021 | 0.2449          | 0.8903 | 0.6536  |
| 0.238         | 54.0  | 3078 | 0.2447          | 0.8894 | 0.6532  |
| 0.238         | 55.0  | 3135 | 0.2446          | 0.8894 | 0.6532  |
| 0.238         | 56.0  | 3192 | 0.2446          | 0.8904 | 0.6536  |
| 0.238         | 57.0  | 3249 | 0.2443          | 0.8894 | 0.6532  |
| 0.238         | 58.0  | 3306 | 0.2441          | 0.8894 | 0.6532  |
| 0.238         | 59.0  | 3363 | 0.2440          | 0.8911 | 0.6566  |
| 0.238         | 60.0  | 3420 | 0.2440          | 0.8911 | 0.6566  |
| 0.238         | 61.0  | 3477 | 0.2439          | 0.8903 | 0.6536  |
| 0.2353        | 62.0  | 3534 | 0.2437          | 0.8911 | 0.6566  |
| 0.2353        | 63.0  | 3591 | 0.2438          | 0.8911 | 0.6566  |
| 0.2353        | 64.0  | 3648 | 0.2437          | 0.8911 | 0.6566  |
| 0.2353        | 65.0  | 3705 | 0.2437          | 0.8911 | 0.6566  |


### Framework versions

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