metadata
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
datasets:
- super_glue
model-index:
- name: boolq_model_v2
results: []
boolq_model_v2
This model is a fine-tuned version of roberta-base on the super_glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.5937
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: 1e-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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.6242 | 1.0 | 590 | 0.5122 |
| 0.4715 | 2.0 | 1180 | 0.4762 |
| 0.3823 | 3.0 | 1770 | 0.5141 |
| 0.3196 | 4.0 | 2360 | 0.5855 |
| 0.2455 | 5.0 | 2950 | 0.5937 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0