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Thought_Intrusive – AI Model by ShayBay | AlphaNeural AI
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ShayBay
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Thought_Intrusive
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transformers
safetensors
deberta-v2
text-classification
generated_from_trainer
microsoft/deberta-v3-small
finetune
mit
text-embeddings-inference
endpoints_compatible
us
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fallacy-model
This model is a fine-tuned version of
microsoft/deberta-v3-small
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: nan
Accuracy: 0.0795
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: 64
eval_batch_size: 64
seed: 42
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
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.0
1.0
1733
nan
0.0795
0.0
2.0
3466
nan
0.0795
0.0
3.0
5199
nan
0.0795
Framework versions
Transformers 5.0.0
Pytorch 2.10.0+cu128
Datasets 4.8.5
Tokenizers 0.22.2
