metadata
base_model: klue/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: pogny-16-0.00002
results: []
pogny-16-0.00002
This model is a fine-tuned version of klue/roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.9029
- Accuracy: 0.7647
- F1: 0.7617
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.1995 | 1.0 | 4818 | 1.4308 | 0.7471 | 0.7452 |
| 0.1231 | 2.0 | 9636 | 1.6541 | 0.7614 | 0.7561 |
| 0.0434 | 3.0 | 14454 | 1.9029 | 0.7647 | 0.7617 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0a0+b5021ba
- Datasets 2.6.2
- Tokenizers 0.14.1