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finetuning-sentiment-model-3000-samples – AI Model by Sara-Jabbour | AlphaNeural AI

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Sara-Jabbour/
finetuning-sentiment-model-3000-samples

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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finetuning-sentiment-model-3000-samples

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

eval_loss: 0.6943
eval_accuracy: 0.48
eval_f1: 0.6389
eval_runtime: 7.4481
eval_samples_per_second: 40.279
eval_steps_per_second: 2.551
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 4.26.1
Pytorch 1.13.1+cu116
Datasets 2.10.1
Tokenizers 0.13.2