metadata
license: cc-by-sa-4.0
base_model: klue/bert-base
tags:
- generated_from_trainer
datasets:
- klue
metrics:
- accuracy
model-index:
- name: bert-base-finetuned-ynat
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: klue
type: klue
config: ynat
split: validation
args: ynat
metrics:
- name: Accuracy
type: accuracy
value: 0.8659273086636653
bert-base-finetuned-ynat
This model is a fine-tuned version of klue/bert-base on the klue dataset. It achieves the following results on the evaluation set:
- Loss: 0.3691
- Accuracy: 0.8659
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: 512
- eval_batch_size: 512
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 90 | 0.4090 | 0.8599 |
| No log | 2.0 | 180 | 0.3929 | 0.8578 |
| No log | 3.0 | 270 | 0.3703 | 0.8648 |
| No log | 4.0 | 360 | 0.3714 | 0.8631 |
| No log | 5.0 | 450 | 0.3691 | 0.8659 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.14.1