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bert-base-uncased-finetuned-removed-0529
This model is a fine-tuned version of YeRyeongLee/bert-base-uncased-finetuned-0505-2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.1501
- Accuracy: 0.8767
- F1: 0.8765
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
No log | 1.0 | 3180 | 0.5072 | 0.8358 | 0.8373 |
No log | 2.0 | 6360 | 0.5335 | 0.8566 | 0.8564 |
No log | 3.0 | 9540 | 0.6317 | 0.8594 | 0.8603 |
No log | 4.0 | 12720 | 0.6781 | 0.8723 | 0.8727 |
No log | 5.0 | 15900 | 0.8235 | 0.8679 | 0.8682 |
No log | 6.0 | 19080 | 0.9205 | 0.8676 | 0.8674 |
No log | 7.0 | 22260 | 0.9898 | 0.8698 | 0.8695 |
0.2348 | 8.0 | 25440 | 1.0756 | 0.8695 | 0.8695 |
0.2348 | 9.0 | 28620 | 1.1342 | 0.8739 | 0.8735 |
0.2348 | 10.0 | 31800 | 1.1501 | 0.8767 | 0.8765 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.9.0
- Datasets 1.16.1
- Tokenizers 0.12.1