m_albert_qa_model
This model is a fine-tuned version of albert-base-v2 on the subjqa dataset. It achieves the following results on the evaluation set:
- Loss: 2.8510
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 32 | 2.6117 |
| No log | 2.0 | 64 | 2.5636 |
| No log | 3.0 | 96 | 2.6828 |
| No log | 4.0 | 128 | 2.8268 |
| No log | 5.0 | 160 | 2.8510 |
Framework versions
- Transformers 4.27.3
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2