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finetuning-DistilBERT-model-4000-samples – AI Model by gent-scholar | AlphaNeural AI

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gent-scholar/
finetuning-DistilBERT-model-4000-samples

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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finetuning-DistilBERT-model-4000-samples

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

eval_loss: 0.2928
eval_accuracy: 0.905
eval_f1: 0.9108
eval_runtime: 8.9839
eval_samples_per_second: 44.524
eval_steps_per_second: 2.783
step: 0

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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2

Framework versions

Transformers 4.25.1
Pytorch 1.13.0+cu116
Tokenizers 0.13.2