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roberta-base-ner-qlorafinetune-runs-32-64 – AI Model by pnr-svc | AlphaNeural AI
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roberta-base-ner-qlorafinetune-runs-32-64
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peft
safetensors
generated_from_trainer
FacebookAI/roberta-base
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mit
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roberta-base-ner-qlorafinetune-runs-32-64
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: 0.1135
Precision: 0.9482
Recall: 0.9690
F1: 0.9585
Accuracy: 0.9845
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: 3.0
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
0.1109
1.0
2643
0.1480
0.9267
0.9538
0.9401
0.9759
0.1136
2.0
5286
0.1192
0.9383
0.9645
0.9512
0.9818
0.0832
3.0
7929
0.1135
0.9482
0.9690
0.9585
0.9845
Framework versions
PEFT 0.12.0
Transformers 4.43.3
Pytorch 2.4.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1
