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muhtasham/
olm-bert-tiny-december-2022-target-glue-qqp

Name: olm-bert-tiny-december-2022-target-glue-qqp
Availability: InStock

generated_from_trainer

apache-2.0

autotrain_compatible

endpoints_compatible

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olm-bert-tiny-december-2022-target-glue-qqp

This model is a fine-tuned version of muhtasham/olm-bert-tiny-december-2022 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.5217
Accuracy: 0.7433
F1: 0.6048

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: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant
training_steps: 5000

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.6283	0.04	500	0.5955	0.6795	0.5186
0.5875	0.09	1000	0.5763	0.6972	0.5596
0.5791	0.13	1500	0.5690	0.6975	0.6011
0.5666	0.18	2000	0.5536	0.7156	0.5520
0.5568	0.22	2500	0.5447	0.7230	0.5709
0.5489	0.26	3000	0.5386	0.7281	0.5665
0.5465	0.31	3500	0.5305	0.7329	0.5917
0.5384	0.35	4000	0.5262	0.7357	0.6231
0.5422	0.4	4500	0.5207	0.7409	0.6200
0.5299	0.44	5000	0.5217	0.7433	0.6048

Framework versions

Transformers 4.27.0.dev0
Pytorch 1.13.1+cu116
Datasets 2.9.1.dev0
Tokenizers 0.13.2

muhtasham/olm-bert-tiny-december-2022-target-glue-qqp

olm-bert-tiny-december-2022-target-glue-qqp

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

muhtasham/
olm-bert-tiny-december-2022-target-glue-qqp