metadata

license: apache-2.0
base_model: bert-base-uncased
tags:
  - generated_from_trainer
metrics:
  - f1
  - accuracy
model-index:
  - name: bert-finetuned-char-classification-e15
    results: []

bert-finetuned-char-classification-e15

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: 0.1233
F1: 0.5572
Roc Auc: 0.7345
Accuracy: 0.3761

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: 0.0002
train_batch_size: 512
eval_batch_size: 512
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
0.1881	1.2	500	0.1694	0.0104	0.5024	0.0007
0.1563	2.39	1000	0.1415	0.3037	0.5948	0.1221
0.1374	3.59	1500	0.1290	0.3997	0.6353	0.1958
0.127	4.78	2000	0.1231	0.4467	0.6579	0.2376
0.1194	5.98	2500	0.1188	0.4801	0.6748	0.2665
0.1114	7.18	3000	0.1183	0.5071	0.6944	0.3016
0.1048	8.37	3500	0.1177	0.5202	0.7032	0.3216
0.0983	9.57	4000	0.1172	0.5344	0.7123	0.3371
0.0917	10.77	4500	0.1164	0.5414	0.7175	0.3458
0.0852	11.96	5000	0.1175	0.5495	0.7240	0.3580
0.0787	13.16	5500	0.1226	0.5545	0.7328	0.3742
0.0738	14.35	6000	0.1233	0.5572	0.7345	0.3761

Framework versions

Transformers 4.31.0
Pytorch 2.0.1+cu118
Datasets 2.14.4
Tokenizers 0.13.3