metadata
base_model: kykim/electra-kor-base
tags:
- generated_from_trainer
datasets:
- nsmc
metrics:
- accuracy
model-index:
- name: electra
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: nsmc
type: nsmc
config: default
split: test
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.91296
electra
This model is a fine-tuned version of kykim/electra-kor-base on the nsmc dataset. It achieves the following results on the evaluation set:
- Loss: 0.2678
- Accuracy: 0.9130
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: 5e-06
- 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: cosine
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.2496 | 1.0 | 9375 | 0.2385 | 0.9072 |
| 0.2108 | 2.0 | 18750 | 0.2496 | 0.9127 |
| 0.1879 | 3.0 | 28125 | 0.2678 | 0.9130 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3