metadata

library_name: transformers
license: apache-2.0
base_model: distilroberta-base
tags:
  - text-classification
  - generated_from_trainer
metrics:
  - accuracy
  - f1
model-index:
  - name: platzi-distilroberta-base-mrpc-glue-hector-nieto
    results: []

platzi-distilroberta-base-mrpc-glue-hector-nieto

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: 0.4723
Accuracy: 0.8407
F1: 0.8889

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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.5407	1.0893	500	0.4723	0.8407	0.8889
0.3421	2.1786	1000	0.6403	0.8480	0.8912

Framework versions

Transformers 4.47.1
Pytorch 2.5.1+cu124
Tokenizers 0.21.0