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---
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
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