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distilbert-base-uncased-qa-boolq – AI Model by andi611 | AlphaNeural AI
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andi611
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distilbert-base-uncased-qa-boolq
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transformers
pytorch
distilbert
text-classification
generated_from_trainer
en
boolq
apache-2.0
autotrain_compatible
endpoints_compatible
us
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distilbert-base-uncased-boolq
This model is a fine-tuned version of
distilbert-base-uncased
on the boolq dataset. It achieves the following results on the evaluation set:
Loss: 1.2071
Accuracy: 0.7315
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: 16
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 1000
num_epochs: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.6506
1.0
531
0.6075
0.6681
0.575
2.0
1062
0.5816
0.6978
0.4397
3.0
1593
0.6137
0.7253
0.2524
4.0
2124
0.8124
0.7466
0.126
5.0
2655
1.1437
0.7370
Framework versions
Transformers 4.8.2
Pytorch 1.8.1+cu111
Datasets 1.8.0
Tokenizers 0.10.3
