metadata
base_model: klue/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: mango-32-0.00002-fin
results: []
mango-32-0.00002-fin
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: 0.9681
- Accuracy: 0.6635
- F1: 0.6551
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: 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 |
---|---|---|---|---|---|
No log | 1.0 | 233 | 0.9796 | 0.6529 | 0.6356 |
No log | 2.0 | 466 | 0.9687 | 0.6541 | 0.6359 |
1.0158 | 3.0 | 699 | 0.9681 | 0.6635 | 0.6551 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0a0+b5021ba
- Datasets 2.6.2
- Tokenizers 0.14.1