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jakub014/
bert-base-uncased-IBM-argQ-30k-finetuned-convincingness-acl2016

Name: bert-base-uncased-IBM-argQ-30k-finetuned-convincingness-acl2016
Availability: InStock

generated_from_trainer

apache-2.0

autotrain_compatible

endpoints_compatible

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bert-base-uncased-IBM-argQ-30k-finetuned-convincingness-acl2016

This model is a fine-tuned version of jakub014/bert-base-uncased-IBM-argQ-30k on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.4143
Accuracy: 0.9266

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: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.3496	1.0	583	0.2207	0.9133
0.1779	2.0	1166	0.2128	0.9159
0.1439	3.0	1749	0.3202	0.9262
0.0903	4.0	2332	0.4013	0.9258
0.051	5.0	2915	0.4143	0.9266

Framework versions

Transformers 4.27.3
Pytorch 1.13.1+cu116
Datasets 2.10.1
Tokenizers 0.13.2

jakub014/bert-base-uncased-IBM-argQ-30k-finetuned-convincingness-acl2016

bert-base-uncased-IBM-argQ-30k-finetuned-convincingness-acl2016

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

jakub014/
bert-base-uncased-IBM-argQ-30k-finetuned-convincingness-acl2016