my_awesome_qa_model
This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.1606
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-06
- train_batch_size: 64
- eval_batch_size: 64
- 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 |
---|---|---|---|
0.8816 | 1.0 | 750 | 1.1553 |
0.8453 | 2.0 | 1500 | 1.1501 |
0.8023 | 3.0 | 2250 | 1.1400 |
0.8053 | 4.0 | 3000 | 1.1513 |
0.7948 | 5.0 | 3750 | 1.1592 |
0.7784 | 6.0 | 4500 | 1.1545 |
0.7721 | 7.0 | 5250 | 1.1519 |
0.7643 | 8.0 | 6000 | 1.1552 |
0.7505 | 9.0 | 6750 | 1.1589 |
0.7537 | 10.0 | 7500 | 1.1606 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
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