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roberta-base-finetuned-ynat_bench – AI Model by Doowon96 | AlphaNeural AI
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Doowon96
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roberta-base-finetuned-ynat_bench
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transformers
safetensors
roberta
text-classification
generated_from_trainer
klue/roberta-base
finetune
autotrain_compatible
endpoints_compatible
us
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roberta-base-finetuned-ynat
This model is a fine-tuned version of
klue/roberta-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.1554
F1: 0.9566
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
lr_scheduler_warmup_steps: 200
num_epochs: 5
Training results
Training Loss
Epoch
Step
Validation Loss
F1
0.6942
0.91
250
0.1847
0.9464
0.1606
1.82
500
0.1518
0.9530
0.1071
2.74
750
0.1496
0.9550
0.0752
3.65
1000
0.1554
0.9566
0.0536
4.56
1250
0.1586
0.9578
Framework versions
Transformers 4.37.2
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.1
