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roberta-finetuned-qa-policy_long – AI Model by peter2000 | AlphaNeural AI
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roberta-finetuned-qa-policy_long
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transformers
tensorboard
safetensors
roberta
question-answering
generated_from_trainer
deepset/roberta-base-squad2
finetune
cc-by-4.0
endpoints_compatible
us
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roberta-finetuned-qa-policy_long
This model is a fine-tuned version of
deepset/roberta-base-squad2
on the None dataset.
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: 0.0002
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 32
total_train_batch_size: 256
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 15
mixed_precision_training: Native AMP
Training results
Framework versions
Transformers 4.35.0
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1
