metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - filter_v2
metrics:
  - f1
  - accuracy
base_model: bert-base-cased
model-index:
  - name: favs_filter_classification_v2
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: filter_v2
          type: filter_v2
          config: default
          split: train
          args: default
        metrics:
          - type: f1
            value: 0.9761904761904762
            name: F1
          - type: accuracy
            value: 0.9545454545454546
            name: Accuracy

favs_filter_classification_v2

This model is a fine-tuned version of bert-base-cased on the filter_v2 dataset. It achieves the following results on the evaluation set:

Loss: 0.2016
F1: 0.9762
Roc Auc: 0.9844
Accuracy: 0.9545

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: 1.5e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
0.6596	1.0	16	0.6086	0.2687	0.5474	0.0
0.5448	2.0	32	0.5354	0.3824	0.6063	0.0
0.5106	3.0	48	0.4874	0.4444	0.6382	0.0455
0.4353	4.0	64	0.4301	0.5352	0.6889	0.1818
0.3699	5.0	80	0.3890	0.6579	0.7640	0.3636
0.349	6.0	96	0.3663	0.6667	0.7633	0.3182
0.3104	7.0	112	0.3327	0.7105	0.7953	0.4545
0.3023	8.0	128	0.2971	0.7733	0.8303	0.5455
0.2676	9.0	144	0.2766	0.8395	0.8861	0.7727
0.2374	10.0	160	0.2541	0.8537	0.8980	0.7727
0.2238	11.0	176	0.2399	0.9024	0.9293	0.8182
0.2084	12.0	192	0.2221	0.9286	0.9531	0.8636
0.2143	13.0	208	0.2138	0.9286	0.9531	0.8636
0.1846	14.0	224	0.2016	0.9762	0.9844	0.9545
0.1812	15.0	240	0.1957	0.9762	0.9844	0.9545
0.1756	16.0	256	0.1881	0.9647	0.9806	0.9091
0.1662	17.0	272	0.1845	0.9762	0.9844	0.9545
0.1715	18.0	288	0.1802	0.9762	0.9844	0.9545
0.1585	19.0	304	0.1782	0.9762	0.9844	0.9545
0.1595	20.0	320	0.1775	0.9762	0.9844	0.9545

Framework versions

Transformers 4.21.1
Pytorch 1.12.1
Datasets 2.4.0
Tokenizers 0.12.1