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bert-base-finetuned-ynat – AI Model by min9805 | AlphaNeural AI
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bert-base-finetuned-ynat
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transformers
pytorch
bert
text-classification
generated_from_trainer
klue/bert-base
finetune
cc-by-sa-4.0
autotrain_compatible
endpoints_compatible
us
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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
