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platzi-distilroberta-base-mrpc-wgcv – AI Model by platzi | AlphaNeural AI | AlphaNeural AI
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platzi-distilroberta-base-mrpc-wgcv
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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-wgcv
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: 0.4053
Accuracy: 0.8358
F1: 0.8847
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: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
Training results
Framework versions
Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1
