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---
license: mit
tags:
- generated_from_trainer
base_model: roberta-base
model-index:
- name: roberta-base-finetuned-squad-v1
results:
- task:
type: question-answering
name: Question Answering
dataset:
name: SQUAD
type: squad
metrics:
- type: f1
value: 92.296
- type: exact_match
value: 86.045
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# roberta-base-finetuned-squad-v1
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the squad dataset.
## Model description
Given a context / content, the model answers to a question by searching the content and extracting the relavant information.
## Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
## Training results
- training loss: 0.77257
## Framework versions
- Transformers 4.27.4
- Pytorch 1.13.1+cu116
- Datasets 2.11.0
- Tokenizers 0.13.3 |