bert_uncased_L-4_H-512_A-8-finetuned-eoir_privacy-longer-finetuned-eoir_privacy-longer30
This model was trained from scratch on the eoir_privacy dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2076
- Accuracy: 0.9491
- F1: 0.8838
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|
| No log | 1.0 | 63 | 0.2446 | 0.9426 | 0.8671 |
| No log | 2.0 | 126 | 0.2306 | 0.9412 | 0.8629 |
| No log | 3.0 | 189 | 0.2637 | 0.9448 | 0.8679 |
| No log | 4.0 | 252 | 0.2375 | 0.9455 | 0.8758 |
| No log | 5.0 | 315 | 0.2423 | 0.9440 | 0.8687 |
| No log | 6.0 | 378 | 0.2571 | 0.9455 | 0.8676 |
| No log | 7.0 | 441 | 0.2040 | 0.9469 | 0.8799 |
| 0.0355 | 8.0 | 504 | 0.2096 | 0.9462 | 0.8784 |
| 0.0355 | 9.0 | 567 | 0.2094 | 0.9448 | 0.8736 |
| 0.0355 | 10.0 | 630 | 0.2076 | 0.9491 | 0.8838 |
Framework versions
- Transformers 4.21.1
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
