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bert-base-finetuned-ynat

Text Classification

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text-embeddings-inference

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bert-base-finetuned-ynat

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

Loss: 1.6806
F1: 0.2273

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: 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	F1
No log	1.0	2	1.8609	0.0476
No log	2.0	4	1.7637	0.0476
No log	3.0	6	1.6806	0.2273
No log	4.0	8	1.6409	0.2273
No log	5.0	10	1.6236	0.2273

Framework versions

Transformers 4.31.0
Pytorch 2.0.1+cu118
Datasets 2.14.0
Tokenizers 0.13.3

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