sentiment_analysis_trainer_model
This model is a fine-tuned version of mdhugol/indonesia-bert-sentiment-classification on an unknown dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.7772
- eval_accuracy: 0.7005
- eval_precision: 0.6482
- eval_recall: 0.7005
- eval_runtime: 6.8809
- eval_samples_per_second: 290.659
- eval_steps_per_second: 36.332
- 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: 0.0001
- 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: 5
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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