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Morality_continuous – AI Model by ajrayman | AlphaNeural AI | AlphaNeural AI
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ajrayman
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Morality_continuous
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transformers
safetensors
roberta
text-classification
generated_from_trainer
FacebookAI/roberta-base
finetune
mit
autotrain_compatible
endpoints_compatible
us
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Morality_continuous
This model is a fine-tuned version of
roberta-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0429
Rmse: 0.2072
Mae: 0.1613
Corr: 0.4707
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: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Rmse
Mae
Corr
No log
1.0
268
0.0534
0.2310
0.1782
0.4636
0.0536
2.0
536
0.0501
0.2238
0.1720
0.4708
0.0536
3.0
804
0.0429
0.2072
0.1613
0.4707
Framework versions
Transformers 4.44.1
Pytorch 1.11.0
Datasets 2.12.0
Tokenizers 0.19.1
