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LR1e4-BS16_Distil-CNN256LSTM128NoBi
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.2466
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: 0.0001
- 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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 3.7339 | 1.0 | 3290 | 2.8528 |
| 1.9078 | 2.0 | 6580 | 1.8196 |
| 1.386 | 3.0 | 9870 | 1.6899 |
| 0.9218 | 4.0 | 13160 | 1.8309 |
| 0.5761 | 5.0 | 16450 | 2.2466 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
