joacorf33
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platzi

Text Classification Transformers PyTorch TensorBoard

roberta generated_from_trainer Eval Results Inference Endpoints

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platzi

This model is a fine-tuned version of distilroberta-base on the datasetX dataset. It achieves the following results on the evaluation set:

Loss: 0.4514
Accuracy: 0.8260
F1: 0.8658

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
0.5383	1.09	500	0.4514	0.8260	0.8658
0.3727	2.18	1000	0.4630	0.8333	0.8764

Framework versions

Transformers 4.27.1
Pytorch 1.13.1+cu116
Datasets 2.10.1
Tokenizers 0.13.2

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Dataset used to train joacorf33/platzi

Evaluation results

Accuracy on datasetX
validation set self-reported

0.826
F1 on datasetX
validation set self-reported

0.866

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