---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: bert-base-uncased-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. -->

# bert-base-uncased-airlines-news-multi-label

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2807
- F1: 0.7124
- Roc Auc: 0.8100
- Accuracy: 0.6766

## 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: 16
- eval_batch_size: 16
- 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| No log        | 1.0   | 118  | 0.2992          | 0.2412 | 0.5680  | 0.5234   |
| No log        | 2.0   | 236  | 0.2628          | 0.5603 | 0.7177  | 0.6255   |
| No log        | 3.0   | 354  | 0.2785          | 0.5691 | 0.7044  | 0.6426   |
| No log        | 4.0   | 472  | 0.2674          | 0.6309 | 0.7619  | 0.6340   |
| 0.2379        | 5.0   | 590  | 0.2640          | 0.6535 | 0.7768  | 0.6340   |
| 0.2379        | 6.0   | 708  | 0.2929          | 0.6596 | 0.7683  | 0.6596   |
| 0.2379        | 7.0   | 826  | 0.2778          | 0.7059 | 0.8189  | 0.6681   |
| 0.2379        | 8.0   | 944  | 0.2807          | 0.7124 | 0.8100  | 0.6766   |
| 0.0507        | 9.0   | 1062 | 0.3381          | 0.6688 | 0.7921  | 0.6511   |
| 0.0507        | 10.0  | 1180 | 0.3160          | 0.6919 | 0.8259  | 0.6468   |
| 0.0507        | 11.0  | 1298 | 0.3206          | 0.7063 | 0.8045  | 0.6936   |
| 0.0507        | 12.0  | 1416 | 0.3273          | 0.6943 | 0.8060  | 0.6766   |
| 0.0115        | 13.0  | 1534 | 0.3408          | 0.6794 | 0.7986  | 0.6638   |
| 0.0115        | 14.0  | 1652 | 0.3488          | 0.6817 | 0.7971  | 0.6681   |
| 0.0115        | 15.0  | 1770 | 0.3469          | 0.6962 | 0.8085  | 0.6766   |
| 0.0115        | 16.0  | 1888 | 0.3517          | 0.6795 | 0.7966  | 0.6596   |
| 0.0045        | 17.0  | 2006 | 0.3537          | 0.6814 | 0.8011  | 0.6596   |
| 0.0045        | 18.0  | 2124 | 0.3566          | 0.6857 | 0.8021  | 0.6638   |
| 0.0045        | 19.0  | 2242 | 0.3587          | 0.6795 | 0.7966  | 0.6596   |
| 0.0045        | 20.0  | 2360 | 0.3596          | 0.6795 | 0.7966  | 0.6596   |


### Framework versions

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