m_bert_base_qa_model
This model is a fine-tuned version of deepset/bert-base-cased-squad2 on the subjqa dataset. It achieves the following results on the evaluation set:
- Loss: 4.4076
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 |
|---|---|---|---|
| No log | 1.0 | 32 | 2.8233 |
| No log | 2.0 | 64 | 2.9102 |
| No log | 3.0 | 96 | 3.2005 |
| No log | 4.0 | 128 | 3.5238 |
| No log | 5.0 | 160 | 3.6986 |
| No log | 6.0 | 192 | 4.0583 |
| No log | 7.0 | 224 | 4.1965 |
| No log | 8.0 | 256 | 4.2924 |
| No log | 9.0 | 288 | 4.4430 |
| No log | 10.0 | 320 | 4.4076 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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