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

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ngasco/
finetuning-sentiment-model-3000-samples

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text-classification

generated_from_trainer

distilbert/distilbert-base-uncased

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 an unknown dataset. It achieves the following results on the evaluation set:

eval_loss: 0.3344
eval_model_preparation_time: 0.0039
eval_accuracy: 0.8733
eval_f1: 0.8766
eval_runtime: 6.4801
eval_samples_per_second: 46.295
eval_steps_per_second: 2.932
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 4.44.2
Pytorch 2.4.1+cu121
Tokenizers 0.19.1