metadata
license: mit
tags:
- generated_from_trainer
datasets:
- squad_v2
- quoref
- adversarial_qa
- duorc
model-index:
- name: rob-base-superqa2
results:
- task:
type: question-answering
name: Question Answering
dataset:
name: squad_v2
type: squad_v2
config: squad_v2
split: validation
metrics:
- name: Exact Match
type: exact_match
value: 79.2365
verified: true
- name: F1
type: f1
value: 82.3326
verified: true
- task:
type: question-answering
name: Question Answering
dataset:
name: adversarial_qa
type: adversarial_qa
config: adversarialQA
split: test
metrics:
- name: Exact Match
type: exact_match
value: 12.4
verified: true
- name: F1
type: f1
value: 12.4
verified: true
- task:
type: question-answering
name: Question Answering
dataset:
name: adversarial_qa
type: adversarial_qa
config: adversarialQA
split: validation
metrics:
- name: Exact Match
type: exact_match
value: 42.3667
verified: true
- name: F1
type: f1
value: 53.3255
verified: true
- task:
type: question-answering
name: Question Answering
dataset:
name: squad
type: squad
config: plain_text
split: validation
metrics:
- name: Exact Match
type: exact_match
value: 86.1925
verified: true
- name: F1
type: f1
value: 92.4306
verified: true
rob-base-superqa2
This model is a fine-tuned version of roberta-base on the None dataset.
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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 256
- total_eval_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2.0
Training results
Framework versions
- Transformers 4.21.1
- Pytorch 1.11.0a0+gita4c10ee
- Datasets 2.4.0
- Tokenizers 0.12.1