bert-base-finetuned-ynat – AI Model by kyeul611 | AlphaNeural AI

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kyeul611/
bert-base-finetuned-ynat

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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bert-base-finetuned-ynat

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

Loss: 0.3817
F1: 0.8673

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: 256
eval_batch_size: 256
seed: 1
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	F1
No log	1.0	179	0.3817	0.8673
No log	2.0	358	0.4065	0.8634
0.2194	3.0	537	0.4077	0.8624
0.2194	4.0	716	0.4443	0.8584
0.2194	5.0	895	0.4795	0.8569
0.1477	6.0	1074	0.5159	0.8570
0.1477	7.0	1253	0.5445	0.8569
0.1477	8.0	1432	0.5711	0.8565
0.0849	9.0	1611	0.5913	0.8542
0.0849	10.0	1790	0.5945	0.8553

Framework versions

Transformers 4.34.1
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1