pytorch roberta text-classification dataset:boolq transformers generated_from_trainer license:mit model-index
---
license: mit
tags:
- generated_from_trainer
datasets:
- boolq
model-index:
- name: roberta-large-finetuned-boolq
  results: []
---

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# roberta-large-finetuned-boolq

This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the boolq dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.3791
- eval_accuracy: 0.8459
- eval_runtime: 95.3733
- eval_samples_per_second: 34.286
- eval_steps_per_second: 4.288
- epoch: 2.0
- step: 588

## 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: 1
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 3

### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
