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# boolq_model

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the super_glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9634

## 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: 8
- eval_batch_size: 8
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 0.6143        | 1.0   | 1179 | 0.5687          |
| 0.4884        | 2.0   | 2358 | 0.4964          |
| 0.3786        | 3.0   | 3537 | 0.5867          |
| 0.3378        | 4.0   | 4716 | 0.8469          |
| 0.3052        | 5.0   | 5895 | 0.9634          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["super_glue"], "base_model": "roberta-base", "model-index": [{"name": "boolq_model", "results": []}]}
transformers tensorboard safetensors roberta text-classification generated_from_trainer dataset:super_glue base_model:roberta-base license:mit autotrain_compatible endpoints_compatible region:us