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bert-base-cased-finetuned-squad-bs_16
This model is a fine-tuned version of bert-base-cased on the squad dataset. It achieves the following results on the evaluation set:
- Loss: 1.3851
- EM: 80.2270
- F1: 88.0794
Overview
Language model: bert-base-cased
Language: English
Downstream-task: Extractive QA
Training data: SQuAD
Eval data: SQuAD
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.0302 | 1.0 | 5546 | 1.0026 |
| 0.7716 | 2.0 | 11092 | 0.9711 |
| 0.5512 | 3.0 | 16638 | 1.1097 |
| 0.3971 | 4.0 | 22184 | 1.2117 |
| 0.2999 | 5.0 | 27730 | 1.3851 |
Framework versions
- Transformers 4.34.0
- Pytorch 1.12.1
- Datasets 2.14.5
- Tokenizers 0.14.1
