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roberta-asap-aes-cv-fold1 – AI Model by BaturalpKorpe | AlphaNeural AI
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roberta-asap-aes-cv-fold1
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transformers
safetensors
generated_from_trainer
FacebookAI/roberta-base
finetune
mit
endpoints_compatible
us
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roberta-asap-aes-cv-fold1
This model is a fine-tuned version of
roberta-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0168
Qwk Meanfisher: 0.7625
Rmse: 1.6990
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: 2.9950908657191678e-05
train_batch_size: 1
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 4
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1878777696731208
num_epochs: 3
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Qwk Meanfisher
Rmse
0.0602
1.0
1947
0.0221
0.6799
1.8849
0.0117
2.0
3894
0.0240
0.7190
2.1041
0.0212
3.0
5841
0.0168
0.7625
1.6990
Framework versions
Transformers 4.57.3
Pytorch 2.9.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1
