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Mukalingam0813/
brand-safety-classifier

Name: brand-safety-classifier
Availability: InStock

safetensors

distilbert

generated_from_trainer

distilbert/distilbert-base-uncased

finetune

apache-2.0

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brand-safety-classifier

This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 2.3403
Accuracy: 0.5726

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: 2e-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
num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	119	2.9720	0.2989
No log	2.0	238	2.2252	0.5179
No log	3.0	357	1.7828	0.5663
No log	4.0	476	1.5521	0.5789
2.2394	5.0	595	1.4689	0.5832
2.2394	6.0	714	1.4107	0.5958
2.2394	7.0	833	1.4512	0.5937
2.2394	8.0	952	1.4819	0.5747
0.7869	9.0	1071	1.4911	0.5832
0.7869	10.0	1190	1.5625	0.5768
0.7869	11.0	1309	1.5715	0.5768
0.7869	12.0	1428	1.6383	0.5789
0.3286	13.0	1547	1.6635	0.5811
0.3286	14.0	1666	1.7684	0.5621
0.3286	15.0	1785	1.8133	0.5684
0.3286	16.0	1904	1.8770	0.5705
0.1571	17.0	2023	1.8929	0.5916
0.1571	18.0	2142	1.9210	0.5811
0.1571	19.0	2261	1.9451	0.5895
0.1571	20.0	2380	2.0018	0.5726
0.1571	21.0	2499	1.9992	0.5768
0.0924	22.0	2618	2.0863	0.5768
0.0924	23.0	2737	2.1038	0.5811
0.0924	24.0	2856	2.1313	0.5747
0.0924	25.0	2975	2.1055	0.5726
0.0752	26.0	3094	2.1162	0.5705
0.0752	27.0	3213	2.1612	0.5705
0.0752	28.0	3332	2.1885	0.5768
0.0752	29.0	3451	2.1585	0.5642
0.0616	30.0	3570	2.2013	0.5768
0.0616	31.0	3689	2.1932	0.5768
0.0616	32.0	3808	2.2058	0.5726
0.0616	33.0	3927	2.2331	0.5705
0.0583	34.0	4046	2.2470	0.5663
0.0583	35.0	4165	2.2558	0.5747
0.0583	36.0	4284	2.2560	0.5747
0.0583	37.0	4403	2.2577	0.5768
0.0483	38.0	4522	2.2817	0.5726
0.0483	39.0	4641	2.2795	0.5789
0.0483	40.0	4760	2.2845	0.5811
0.0483	41.0	4879	2.3065	0.5789
0.0483	42.0	4998	2.3018	0.5747
0.0474	43.0	5117	2.3147	0.5789
0.0474	44.0	5236	2.3279	0.5768
0.0474	45.0	5355	2.3330	0.5768
0.0474	46.0	5474	2.3449	0.5726
0.0422	47.0	5593	2.3433	0.5789
0.0422	48.0	5712	2.3418	0.5726
0.0422	49.0	5831	2.3411	0.5747
0.0422	50.0	5950	2.3403	0.5726

Framework versions

Transformers 4.44.0
Pytorch 2.4.0
Datasets 2.20.0
Tokenizers 0.19.1

Mukalingam0813/brand-safety-classifier

brand-safety-classifier

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Mukalingam0813/
brand-safety-classifier