metadata
base_model: klue/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: pogny_5_128_0.01
results: []
pogny_5_128_0.01
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: 1.6856
- 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: 0.01
- train_batch_size: 128
- eval_batch_size: 128
- 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 | Accuracy | F1 |
|---|---|---|---|---|---|
| 2.3955 | 1.0 | 603 | 1.8993 | 0.4376 | 0.2665 |
| 2.1177 | 2.0 | 1206 | 2.1650 | 0.4376 | 0.2665 |
| 2.0063 | 3.0 | 1809 | 2.1854 | 0.4376 | 0.2665 |
| 1.8805 | 4.0 | 2412 | 1.8213 | 0.4376 | 0.2665 |
| 1.7214 | 5.0 | 3015 | 1.6856 | 0.4376 | 0.2665 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.2.2
- Datasets 2.19.1
- Tokenizers 0.19.1