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roberta-base-product-related – AI Model by SF001-123456 | AlphaNeural AI
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SF001-123456
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roberta-base-product-related
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peft
tensorboard
safetensors
roberta
text-classification
adapter
lora
transformers
FacebookAI/roberta-base
adapter
mit
us
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roberta-base-product-related
This model is a fine-tuned version of
roberta-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.1125
Accuracy: 0.9713
Precision: 0.9559
Recall: 0.9894
F1: 0.9723
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: 16
eval_batch_size: 16
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
Precision
Recall
F1
0.1808
1.0
3360
0.1271
0.9631
0.9464
0.9834
0.9645
0.1033
2.0
6720
0.1151
0.9691
0.9521
0.9892
0.9703
0.1365
3.0
10080
0.1125
0.9713
0.9559
0.9894
0.9723
Framework versions
PEFT 0.17.1
Transformers 4.55.4
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.21.4
