metadata
base_model: klue/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: pogny-64-0.005
results: []
pogny-64-0.005
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: 1.6848
- Accuracy: 0.4376
- F1: 0.2665
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: 0.005
- 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
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 1.9411 | 1.0 | 1205 | 2.0029 | 0.0643 | 0.0078 |
| 1.8423 | 2.0 | 2410 | 1.7954 | 0.2545 | 0.1032 |
| 1.7098 | 3.0 | 3615 | 1.6848 | 0.4376 | 0.2665 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0a0+b5021ba
- Datasets 2.6.2
- Tokenizers 0.14.1