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implicit-motives-power-roberta-large – AI Model by theharmonylab | AlphaNeural AI
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implicit-motives-power-roberta-large
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safetensors
roberta
generated_from_trainer
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schone-power
FacebookAI/roberta-large
finetune
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This model is a fine-tuned version of
roberta-large
on the GLUE SCHONE_POW dataset. It achieves the following results on the evaluation set:
Loss: 0.1556
Roc Auc: 0.9742
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: 1e-05
train_batch_size: 128
eval_batch_size: 256
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 256
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5.0
Training results
Training Loss
Epoch
Step
Validation Loss
Roc Auc
0.2924
0.9985
332
0.2605
0.9248
0.2553
2.0
665
0.2234
0.9468
0.2317
2.9985
997
0.1899
0.9620
0.2063
4.0
1330
0.1645
0.9715
0.1897
4.9925
1660
0.1556
0.9742
Framework versions
Transformers 4.44.0.dev0
Pytorch 2.0.1+cu118
Datasets 2.20.0
Tokenizers 0.19.1
