metadata
library_name: transformers
base_model: skt/kobert-base-v1
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: skt-bert
results: []
skt-bert
This model is a fine-tuned version of skt/kobert-base-v1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1823
- Accuracy: 0.5493
- F1: 0.5403
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 483 | 1.2325 | 0.5348 | 0.5259 |
| No log | 2.0 | 966 | 1.1823 | 0.5493 | 0.5403 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1