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my_qa_model_1
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.4752
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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- 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 | 0.96 | 3 | 5.6227 |
| No log | 1.96 | 6 | 5.1169 |
| No log | 2.96 | 9 | 4.5577 |
| No log | 3.96 | 12 | 3.9969 |
| No log | 4.96 | 15 | 3.5279 |
| No log | 5.96 | 18 | 3.1371 |
| No log | 6.96 | 21 | 2.8468 |
| No log | 7.96 | 24 | 2.6456 |
| No log | 8.96 | 27 | 2.5241 |
| No log | 9.96 | 30 | 2.4752 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.13.0
- Datasets 1.16.1
- Tokenizers 0.10.3
