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transfer-learning – AI Model by SednaWorld | AlphaNeural AI
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SednaWorld
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transfer-learning
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transformers
pytorch
tensorboard
roberta
text-classification
generated_from_trainer
apache-2.0
autotrain_compatible
endpoints_compatible
us
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Model card
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transfer-learning
This model is a fine-tuned version of
distilroberta-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.7182
Accuracy: 0.8064
F1: 0.8460
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
Accuracy
F1
0.5176
1.09
500
0.7127
0.8015
0.8541
0.3704
2.18
1000
0.7182
0.8064
0.8460
Framework versions
Transformers 4.30.2
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.13.3
