qa_model_study_1
This model is a fine-tuned version of distilbert-base-uncased on the sberquad dataset. It achieves the following results on the evaluation set:
- Loss: 2.4337
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 3.1351 | 1.0 | 750 | 2.6338 |
| 2.5385 | 2.0 | 1500 | 2.4813 |
| 2.3433 | 3.0 | 2250 | 2.4337 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for konstaya/qa_model_study_1
Base model
distilbert/distilbert-base-uncased