metadata
tags:
- generated_from_trainer
datasets:
- klue
metrics:
- pearsonr
model-index:
- name: bert-base-finetuned-sts
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: klue
type: klue
config: sts
split: train
args: sts
metrics:
- name: Pearsonr
type: pearsonr
value: 0.8792156464193064
bert-base-finetuned-sts
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: 0.5353
- Pearsonr: 0.8792
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: 256
- eval_batch_size: 256
- 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 | Pearsonr |
|---|---|---|---|---|
| No log | 1.0 | 46 | 0.8265 | 0.8153 |
| No log | 2.0 | 92 | 0.8016 | 0.8500 |
| No log | 3.0 | 138 | 0.6058 | 0.8729 |
| No log | 4.0 | 184 | 0.5353 | 0.8792 |
| No log | 5.0 | 230 | 0.5959 | 0.8763 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2