distilbert-base-uncased-finetuned-custom
This model is a fine-tuned version of bert-large-uncased-whole-word-masking-finetuned-squad on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7808
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
- 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 |
|---|---|---|---|
| No log | 1.0 | 368 | 1.1128 |
| 2.1622 | 2.0 | 736 | 0.8494 |
| 1.2688 | 3.0 | 1104 | 0.7808 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 1.18.4
- Tokenizers 0.11.6