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roberta-base_fold_2 – AI Model by OliverHeine | AlphaNeural AI
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OliverHeine
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roberta-base_fold_2
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transformers
safetensors
roberta
text-classification
generated_from_trainer
FacebookAI/roberta-base
finetune
mit
text-embeddings-inference
endpoints_compatible
us
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roberta-base_fold_2
This model is a fine-tuned version of
roberta-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0307
Accuracy: 0.9940
F1: 0.9888
Precision: 0.9942
Recall: 0.9835
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: 38
eval_batch_size: 38
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
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
Precision
Recall
0.0404
1.0
3983
0.0300
0.9931
0.9871
0.9953
0.9791
0.0372
2.0
7966
0.0291
0.9936
0.9882
0.9931
0.9833
0.0418
3.0
11949
0.0307
0.9940
0.9888
0.9942
0.9835
Framework versions
Transformers 5.3.0
Pytorch 2.10.0+cu128
Datasets 4.6.1
Tokenizers 0.22.2
