metadata
base_model: klue/roberta-large
tags:
- generated_from_trainer
datasets:
- klue
metrics:
- accuracy
- f1
model-index:
- name: nli_roberta-large_lr1e-05_wd1e-03_ep3_ckpt
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: klue
type: klue
config: nli
split: validation
args: nli
metrics:
- name: Accuracy
type: accuracy
value: 0.9026666666666666
- name: F1
type: f1
value: 0.9025716877431428
nli_roberta-large_lr1e-05_wd1e-03_ep3_ckpt
This model is a fine-tuned version of klue/roberta-large on the klue dataset. It achieves the following results on the evaluation set:
- Loss: 0.3425
- Accuracy: 0.9027
- F1: 0.9026
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: 1e-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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.5725 | 1.0 | 391 | 0.3381 | 0.8813 | 0.8811 |
| 0.2182 | 2.0 | 782 | 0.3055 | 0.898 | 0.8979 |
| 0.112 | 3.0 | 1173 | 0.3425 | 0.9027 | 0.9026 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.13.0
- Tokenizers 0.13.3