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bert-finetuned-squad
Skier8402/bert-finetuned-squad
bert-finetuned-squad is a question answering model from Skier8402. Use it when the input is a question plus a passage. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Question Answering
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Mar 6, 2024
- Updated
- Mar 6, 2024
- SHA
- 1ce7b94b
Try a prompt
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
bert-finetuned-squad
This model is a fine-tuned version of bert-base-cased on the SQUAD dataset.
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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Step | Training Loss |
|---|---|
| 500 | 2.6355 |
| 1000 | 1.6559 |
| 1500 | 1.4608 |
| 2000 | 1.3781 |
| 2500 | 1.3286 |
| 3000 | 1.2879 |
| 3500 | 1.2369 |
| 4000 | 1.1795 |
| 4500 | 1.1303 |
| 5000 | 1.1637 |
| 5500 | 1.1227 |
| 6000 | 1.1406 |
| 6500 | 1.1413 |
| 7000 | 1.0821 |
| 7500 | 1.0964 |
| 8000 | 1.1083 |
| 8500 | 1.0583 |
| 9000 | 1.0825 |
| 9500 | 1.0264 |
| 10000 | 1.0407 |
| 10500 | 1.0352 |
| 11000 | 1.0107 |
| 11500 | 0.8077 |
| 12000 | 0.7105 |
| 12500 | 0.7843 |
| 13000 | 0.7401 |
| 13500 | 0.7716 |
| 14000 | 0.7772 |
| 14500 | 0.749 |
| 15000 | 0.7348 |
| 15500 | 0.7495 |
| 16000 | 0.7756 |
| 16500 | 0.7243 |
| 17000 | 0.7683 |
| 17500 | 0.7536 |
| 18000 | 0.7329 |
| 18500 | 0.7342 |
| 19000 | 0.6998 |
| 19500 | 0.7326 |
| 20000 | 0.7646 |
| 20500 | 0.7729 |
| 21000 | 0.734 |
| 21500 | 0.734 |
| 22000 | 0.691 |
| 22500 | 0.5887 |
| 23000 | 0.5148 |
| 23500 | 0.539 |
| 24000 | 0.5159 |
| 24500 | 0.4908 |
| 25000 | 0.5242 |
| 25500 | 0.5162 |
| 26000 | 0.4862 |
| 26500 | 0.526 |
| 27000 | 0.4953 |
| 27500 | 0.5276 |
| 28000 | 0.4848 |
| 28500 | 0.4863 |
| 29000 | 0.5222 |
| 29500 | 0.5192 |
| 30000 | 0.5088 |
| 30500 | 0.5167 |
| 31000 | 0.4906 |
| 31500 | 0.5161 |
| 32000 | 0.4995 |
| 32500 | 0.4961 |
| 33000 | 0.4653 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2
- Task
- Question Answering
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Mar 6, 2024
- Updated
- Mar 6, 2024