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Hasil Sentimen Distilbert

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set: Loss: 0.5781 Accuracy: 0.891

TipoOtherModelo basedistilbert-base-uncasedVersãoRevision 4785e62Publicador@Kenz13Cnota

Fonte do modelo

Tipo
Other
Tamanho do arquivo
255 MB
Modelo base
distilbert-base-uncased
Versão
vRevision 4785e62
Atualizado
15 de set. de 2026
Publicador
@Kenz13
Downloads
5
Fonte
Hugging Face

Descrição da fonte

hasil-sentimen-distilbert

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

  • Loss: 0.5781
  • Accuracy: 0.891

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: 32
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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 LossEpochStepValidation LossAccuracy
No log1.01570.76520.841
No log2.03140.58000.887
No log3.04710.57810.891

Framework versions

  • Transformers 5.0.0
  • Pytorch 2.10.0+cu128
  • Datasets 4.8.3
  • Tokenizers 0.22.2

Fontes

1 fonte
Hugging FacePrimárioVersão 4785e62d70059afa93c5d0efab3548385e816494
huggingface.co/Kenz13/hasil-sentimen-distilbert/tree/4785e62d70059afa93c5d0efab3548385e816494

Verificado 9 de ago.

Artefatos de modelo

1 artefato

model.safetensors

safetensors · 255 MB · SHA-256 ae1285540f2d…b7a4 · Hugging Face

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Trechos de fonte

3 trechos

--- library_name: transformers license: apache-2.0 base_model: distilbert-base-uncased tags: - generated_from_trainer metrics: - accuracy model-index: - name: hasil-sentimen-distilbert results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # hasil-sentimen-distilbert This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.5781 - Accuracy: 0.891 ## 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: 32 - eval_batch_size: 16 - seed: 42 - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 157 | 0.7652 | 0.841 | | No log | 2.0 | 314 | 0.5800 | 0.887 | | No log | 3.0 | 471 | 0.5781 | 0.891 | ### Framework versions - Transformers 5.0.0 - Pytorch 2.10.0+cu128 - Datasets 4.8.3 - Tokenizers 0.22.2

Source context: 5 downloads · 0 likes · Pipeline text-classification · Library transformers · Repo Kenz13/hasil-sentimen-distilbert

Source context: 1 downloads · 0 likes · Pipeline text-classification · Library transformers · Repo Kenz13/hasil-sentimen-distilbert