lexglue-unfair-tos – AI Model by marmolpen3 | AlphaNeural AI

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marmolpen3/
lexglue-unfair-tos

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text-classification

generated_from_trainer

google-bert/bert-base-uncased

autotrain_compatible

endpoints_compatible

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lexglue-unfair-tos

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

Loss: 0.0314
Macro-f1: 0.7675
Micro-f1: 0.9531

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: 3e-05
train_batch_size: 8
eval_batch_size: 8
seed: 1
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 20.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Macro-f1	Micro-f1
0.0994	1.0	692	0.0443	0.4100	0.9246
0.0453	2.0	1384	0.0281	0.5823	0.9384
0.0205	3.0	2076	0.0253	0.7639	0.9474
0.0133	4.0	2768	0.0265	0.7521	0.9462
0.0092	5.0	3460	0.0280	0.7430	0.9401
0.0062	6.0	4152	0.0278	0.7611	0.9488
0.0049	7.0	4844	0.0292	0.7492	0.9431
0.0032	8.0	5536	0.0314	0.7675	0.9531
0.0025	9.0	6228	0.0316	0.7549	0.9498
0.0022	10.0	6920	0.0347	0.7404	0.9481
0.0016	11.0	7612	0.0333	0.7628	0.9514

Framework versions

Transformers 4.44.2
Pytorch 2.1.2+cu121
Datasets 3.0.2
Tokenizers 0.19.1