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CSQA_roberta_large – AI Model by gulsmyigit | AlphaNeural AI
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CSQA_roberta_large
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transformers
tensorboard
safetensors
roberta
multiple-choice
generated_from_trainer
FacebookAI/roberta-large
finetune
mit
endpoints_compatible
us
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This model is a fine-tuned version of
FacebookAI/roberta-large
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.6847
Accuracy: 0.7232
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: 1e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.98) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 150
num_epochs: 3
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
No log
0.9984
304
0.9992
0.6224
1.352
1.9984
608
0.7015
0.7150
1.352
2.9984
912
0.6847
0.7232
Framework versions
Transformers 4.52.0.dev0
Pytorch 2.6.0+cu124
Datasets 3.5.2.dev0
Tokenizers 0.21.1
