klue-bert-finetuned-nsmc
This model is a fine-tuned version of klue/bert-base on the nsmc dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.2402
- eval_accuracy: 0.9029
- eval_f1: 0.9029
- eval_runtime: 343.6707
- eval_samples_per_second: 145.488
- eval_steps_per_second: 4.548
- epoch: 1.0
- step: 4688
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: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Framework versions
- Transformers 4.13.0
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.10.3
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