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platzi-distilroberta-base-mrpc-glue-jcms-bits – AI Model by platzi | AlphaNeural AI
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platzi
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platzi-distilroberta-base-mrpc-glue-jcms-bits
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transformers
tensorboard
safetensors
roberta
text-classification
generated_from_trainer
distilbert/distilroberta-base
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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platzi-distilroberta-base-mrpc-glue-jcms-bits
This model is a fine-tuned version of
distilroberta-base
on the glue and the mrpc datasets. It achieves the following results on the evaluation set:
Loss: 0.4084
Accuracy: 0.8382
F1: 0.8821
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: 8
eval_batch_size: 8
seed: 42
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
F1
0.556
1.09
500
0.4084
0.8382
0.8821
0.3759
2.18
1000
0.6064
0.8260
0.8711
Framework versions
Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.1
