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distilbert-base-uncased-finetuned-mrpc-test – AI Model by hwaQing | AlphaNeural AI
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distilbert-base-uncased-finetuned-mrpc-test
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transformers
pytorch
tensorboard
distilbert
text-classification
generated_from_trainer
glue
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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distilbert-base-uncased-finetuned-mrpc
This model is a fine-tuned version of
distilbert-base-uncased
on the glue dataset. It achieves the following results on the evaluation set:
Loss: 0.5708
Accuracy: 0.7034
F1: 0.8207
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: 2e-05
train_batch_size: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 1
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
No log
1.0
58
0.5708
0.7034
0.8207
Framework versions
Transformers 4.10.2
Pytorch 1.9.0+cu102
Datasets 1.11.0
Tokenizers 0.10.3
