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QA_BERT_16_epoch
farid1088/QA_BERT_16_epoch
QA_BERT_16_epoch is a question answering model from farid1088. Use it when the input is a question plus a passage. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Question Answering
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Mar 2, 2024
- Updated
- Mar 2, 2024
- SHA
- f572d1a3
Try a prompt
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. -->
QA_BERT_16_epoch
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.2513
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: 160
- eval_batch_size: 80
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 16
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 2 | 5.5606 |
| No log | 2.0 | 4 | 4.7705 |
| No log | 3.0 | 6 | 4.1022 |
| No log | 4.0 | 8 | 3.7775 |
| No log | 5.0 | 10 | 3.6740 |
| No log | 6.0 | 12 | 3.6632 |
| No log | 7.0 | 14 | 3.5963 |
| No log | 8.0 | 16 | 3.5161 |
| No log | 9.0 | 18 | 3.4593 |
| No log | 10.0 | 20 | 3.4122 |
| No log | 11.0 | 22 | 3.3449 |
| No log | 12.0 | 24 | 3.3252 |
| No log | 13.0 | 26 | 3.3158 |
| No log | 14.0 | 28 | 3.2810 |
| No log | 15.0 | 30 | 3.2449 |
| No log | 16.0 | 32 | 3.2513 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.14.7
- Tokenizers 0.15.0
- Task
- Question Answering
- Library
- transformers
- Type
- bert
- Created
- Mar 2, 2024
- Updated
- Mar 2, 2024