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platzi-diltilroberta-base-mrpc-glue-santiago-toledo – AI Model by SantiagoTB | AlphaNeural AI
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SantiagoTB
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platzi-diltilroberta-base-mrpc-glue-santiago-toledo
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transformers
pytorch
roberta
text-classification
generated_from_trainer
glue
distilbert/distilroberta-base
finetune
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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platzi-diltilroberta-base-mrpc-glue-santiago-toledo
This model is a fine-tuned version of
distilroberta-base
on the datasetX dataset. It achieves the following results on the evaluation set:
Loss: 0.6731
Accuracy: 0.8284
F1: 0.8723
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
0.4044
1.09
500
0.6731
0.8284
0.8723
0.231
2.18
1000
0.8025
0.8260
0.8748
Framework versions
Transformers 4.31.0
Pytorch 2.0.1+cpu
Datasets 2.14.4
Tokenizers 0.13.3
