boolq_deberta_model
This model is a fine-tuned version of microsoft/deberta-v3-base on the super_glue - boolq dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.4066
- eval_accuracy: 0.8468
- eval_runtime: 111.0255
- eval_samples_per_second: 29.453
- eval_steps_per_second: 1.846
- epoch: 2.0
- step: 1180
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: 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: 3
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
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