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RoBERTa_Test_Training – AI Model by ICT2214Team7 | AlphaNeural AI
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RoBERTa_Test_Training
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transformers
tensorboard
safetensors
roberta
token-classification
generated_from_trainer
conll2003
distilbert/distilroberta-base
finetune
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
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RoBERTa_Test_Training
This model is a fine-tuned version of
distilroberta-base
on the conll2003 dataset. It achieves the following results on the evaluation set:
Loss: 0.0590
Precision: 0.9508
Recall: 0.9550
F1: 0.9529
Accuracy: 0.9880
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: 5e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
0.0803
1.0
1756
0.0725
0.9236
0.9313
0.9274
0.9820
0.0373
2.0
3512
0.0627
0.9453
0.9487
0.9470
0.9868
0.0213
3.0
5268
0.0590
0.9508
0.9550
0.9529
0.9880
Framework versions
Transformers 4.40.2
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1
