my_awesome_wnut_model
This model is a fine-tuned version of bert-base-cased on the wnut_17 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3958
- Precision: 0.55
- Recall: 0.3772
- F1: 0.4475
- Accuracy: 0.9481
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: 16
- eval_batch_size: 16
- seed: 42
- 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 | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 213 | 0.2562 | 0.5704 | 0.2929 | 0.3870 | 0.9417 |
No log | 2.0 | 426 | 0.2776 | 0.5462 | 0.3179 | 0.4019 | 0.9436 |
0.1469 | 3.0 | 639 | 0.2834 | 0.5453 | 0.3624 | 0.4354 | 0.9475 |
0.1469 | 4.0 | 852 | 0.3004 | 0.5669 | 0.3652 | 0.4442 | 0.9480 |
0.0325 | 5.0 | 1065 | 0.3360 | 0.5858 | 0.3735 | 0.4561 | 0.9482 |
0.0325 | 6.0 | 1278 | 0.3471 | 0.5149 | 0.3855 | 0.4409 | 0.9474 |
0.0325 | 7.0 | 1491 | 0.3883 | 0.5552 | 0.3633 | 0.4392 | 0.9474 |
0.0117 | 8.0 | 1704 | 0.3881 | 0.5602 | 0.3707 | 0.4462 | 0.9477 |
0.0117 | 9.0 | 1917 | 0.4008 | 0.5582 | 0.3689 | 0.4442 | 0.9478 |
0.0051 | 10.0 | 2130 | 0.3958 | 0.55 | 0.3772 | 0.4475 | 0.9481 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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Finetuned from
Dataset used to train galaxy78/my_awesome_wnut_model
Evaluation results
- Precision on wnut_17test set self-reported0.550
- Recall on wnut_17test set self-reported0.377
- F1 on wnut_17test set self-reported0.447
- Accuracy on wnut_17test set self-reported0.948