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sentiment_roberta_large_with_diary
This model is a fine-tuned version of klue/roberta-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5671
- Micro f1 score: 80.0000
- Auprc: 77.0282
- Accuracy: 0.8
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Micro f1 score | Auprc | Accuracy |
|---|---|---|---|---|---|---|
| 1.6198 | 0.13 | 100 | 1.3872 | 48.9362 | 55.5743 | 0.4894 |
| 0.6603 | 0.26 | 200 | 0.9249 | 65.9574 | 62.8759 | 0.6596 |
| 0.5387 | 0.4 | 300 | 0.7262 | 73.1915 | 71.1936 | 0.7319 |
| 0.4801 | 0.53 | 400 | 0.6623 | 74.0426 | 68.8606 | 0.7404 |
| 0.4597 | 0.66 | 500 | 0.6092 | 76.1702 | 75.7346 | 0.7617 |
| 0.4217 | 0.79 | 600 | 0.5929 | 78.7234 | 76.8709 | 0.7872 |
| 0.4148 | 0.93 | 700 | 0.5671 | 80.0000 | 77.0282 | 0.8 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2
