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Finetuned_bert_model – AI Model by Winnie-Kay | AlphaNeural AI
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Winnie-Kay
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Finetuned_bert_model
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transformers
pytorch
tensorboard
roberta
text-classification
generated_from_trainer
mit
autotrain_compatible
endpoints_compatible
us
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Finetuned_bert_model
This model is a fine-tuned version of
roberta-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.5644
Rmse: 0.6048
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: 3e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 4
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Rmse
0.6429
4.0
500
0.5644
0.6048
Framework versions
Transformers 4.29.0
Pytorch 2.0.0+cu118
Datasets 2.12.0
Tokenizers 0.13.3
