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KcELECTRA-base-v2022-KEmoFact-EFE-0927
This model is a fine-tuned version of beomi/KcELECTRA-base-v2022 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5879
- Precision: 0.4052
- Recall: 0.4497
- F1: 0.4263
- Ov Accuracy: 0.8253
- Jaccard: 0.7374
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- 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 | Precision | Recall | F1 | Ov Accuracy | Jaccard |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 414 | 0.4141 | 0.3382 | 0.3897 | 0.3622 | 0.8209 | 0.6966 |
| 0.4519 | 2.0 | 828 | 0.4230 | 0.3456 | 0.3988 | 0.3703 | 0.8211 | 0.7086 |
| 0.302 | 3.0 | 1242 | 0.4758 | 0.3660 | 0.4208 | 0.3915 | 0.8204 | 0.7164 |
| 0.2037 | 4.0 | 1656 | 0.5589 | 0.3649 | 0.4083 | 0.3854 | 0.8193 | 0.7084 |
| 0.1394 | 5.0 | 2070 | 0.6199 | 0.3533 | 0.4089 | 0.3791 | 0.8148 | 0.7064 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
