cfr-qa-model
This model is a fine-tuned version of distilbert/distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.9458
- Exact Match: 0.0
- F1: 0.0
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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Exact Match | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 5 | 4.7252 | 0.0 | 0.0 |
| No log | 2.0 | 10 | 3.5616 | 0.0 | 0.0 |
| No log | 3.0 | 15 | 2.9458 | 0.0 | 0.0 |
Framework versions
- Transformers 4.55.0
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.4
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Model tree for AsherArmstrong/cfr-qa-model
Base model
distilbert/distilbert-base-uncased