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longformer-medqa-usmle-nocontext – AI Model by GBaker | AlphaNeural AI
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longformer-medqa-usmle-nocontext
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transformers
pytorch
tensorboard
longformer
multiple-choice
generated_from_trainer
endpoints_compatible
us
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longformer_model_nocontext
This model is a fine-tuned version of
allenai/longformer-base-4096
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 1.3861
Accuracy: 0.2467
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: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
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
1.3896
1.0
636
1.3861
0.2482
1.39
2.0
1272
1.3860
0.2459
1.3885
3.0
1908
1.3861
0.2467
Framework versions
Transformers 4.26.0
Pytorch 1.13.1+cu116
Datasets 2.8.0
Tokenizers 0.13.2
