my_awesome_qa_model
This model is a fine-tuned version of bert-base-uncased on the squad dataset. It achieves the following results on the evaluation set:
- Loss: 3.5143
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: 5e-05
- train_batch_size: 40
- eval_batch_size: 40
- 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 |
|---|---|---|---|
| No log | 1.0 | 100 | 4.7435 |
| No log | 2.0 | 200 | 4.3343 |
| No log | 3.0 | 300 | 4.0804 |
| No log | 4.0 | 400 | 3.8983 |
| 4.3932 | 5.0 | 500 | 3.7642 |
| 4.3932 | 6.0 | 600 | 3.6649 |
| 4.3932 | 7.0 | 700 | 3.5978 |
| 4.3932 | 8.0 | 800 | 3.5499 |
| 4.3932 | 9.0 | 900 | 3.5216 |
| 3.7318 | 10.0 | 1000 | 3.5143 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.0
- Datasets 2.12.0
- Tokenizers 0.13.3
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Model tree for NightMachinery/my_awesome_qa_model
Base model
google-bert/bert-base-uncased