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roberta-base-ner-lorafinetune-runs-128-256 – AI Model by pnr-svc | AlphaNeural AI
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pnr-svc
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roberta-base-ner-lorafinetune-runs-128-256
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peft
tensorboard
safetensors
generated_from_trainer
FacebookAI/roberta-base
adapter
mit
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roberta-base-ner-lorafinetune-runs-128-256
This model is a fine-tuned version of
FacebookAI/roberta-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.1077
Precision: 0.9467
Recall: 0.9671
F1: 0.9568
Accuracy: 0.9829
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: 0.0004
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
0.1184
1.0
2643
0.1542
0.9368
0.9538
0.9452
0.9755
0.1116
2.0
5286
0.1153
0.9401
0.9633
0.9515
0.9804
0.0812
3.0
7929
0.1077
0.9467
0.9671
0.9568
0.9829
Framework versions
PEFT 0.12.0
Transformers 4.43.3
Pytorch 2.4.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1
