metadata
tags:
- generated_from_trainer
datasets:
- klue
metrics:
- pearsonr
- f1
model-index:
- name: bert-base-finetuned-sts
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: klue
type: klue
args: sts
metrics:
- name: Pearsonr
type: pearsonr
value: 0.8756147003619346
- name: F1
type: f1
value: 0.8416666666666667
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: 0.4115
- Pearsonr: 0.8756
- F1: 0.8417
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-05
- train_batch_size: 32
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Pearsonr | F1 |
|---|---|---|---|---|---|
| 0.7836 | 1.0 | 365 | 0.5507 | 0.8435 | 0.8121 |
| 0.1564 | 2.0 | 730 | 0.4396 | 0.8495 | 0.8136 |
| 0.0989 | 3.0 | 1095 | 0.4115 | 0.8756 | 0.8417 |
| 0.0682 | 4.0 | 1460 | 0.4466 | 0.8746 | 0.8449 |
Framework versions
- Transformers 4.10.2
- Pytorch 1.7.1
- Datasets 1.12.1
- Tokenizers 0.10.3