metadata

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: []

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

This model is a fine-tuned version of 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