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bert-base-cased-finetuned-on-REDv2_EN
This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3211
- F1: 0.6645
- Roc Auc: 0.7973
- Accuracy: 0.5433
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: 2
- total_train_batch_size: 16
- 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 | F1 | Roc Auc | Accuracy |
---|---|---|---|---|---|---|
No log | 1.0 | 255 | 0.2900 | 0.5649 | 0.7096 | 0.4144 |
0.3267 | 2.0 | 511 | 0.2591 | 0.6257 | 0.7545 | 0.5064 |
0.3267 | 3.0 | 766 | 0.2548 | 0.6655 | 0.7841 | 0.5672 |
0.1654 | 4.0 | 1022 | 0.2654 | 0.6574 | 0.7844 | 0.5433 |
0.1654 | 5.0 | 1277 | 0.2793 | 0.6718 | 0.7963 | 0.5654 |
0.0906 | 6.0 | 1533 | 0.2919 | 0.6667 | 0.7929 | 0.5562 |
0.0906 | 7.0 | 1788 | 0.3026 | 0.6716 | 0.8009 | 0.5525 |
0.0561 | 8.0 | 2044 | 0.3122 | 0.6661 | 0.7973 | 0.5543 |
0.0561 | 9.0 | 2299 | 0.3185 | 0.6678 | 0.7998 | 0.5414 |
0.0394 | 9.98 | 2550 | 0.3211 | 0.6645 | 0.7973 | 0.5433 |
Framework versions
- Transformers 4.27.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2