File size: 2,265 Bytes
4478821
 
 
 
d079334
 
 
 
 
 
 
4478821
 
bf9c36b
 
 
 
 
 
 
 
 
 
d079334
bf9c36b
d079334
bf9c36b
d079334
bf9c36b
d079334
bf9c36b
92d1d2a
 
 
 
 
 
 
 
 
d079334
92d1d2a
d079334
92d1d2a
d079334
92d1d2a
d079334
92d1d2a
e49ab07
 
 
 
 
 
 
 
 
d079334
e49ab07
d079334
e49ab07
d079334
e49ab07
d079334
e49ab07
4478821
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
---
license: mit
tags:
- generated_from_trainer
datasets:
- squad_v2
- quoref
- adversarial_qa
- ibm/duorc
task:
- question-answering
model-index:
- name: rob-base-superqa
  results:
  - task:
      type: question-answering
      name: Question Answering
    dataset:
      name: adversarial_qa
      type: adversarial_qa
      config: adversarialQA
      split: validation
    metrics:
    - type: exact_match
      value: 43.8667
      name: Exact Match
      verified: true
    - type: f1
      value: 55.135
      name: F1
      verified: true
  - task:
      type: question-answering
      name: Question Answering
    dataset:
      name: squad_v2
      type: squad_v2
      config: squad_v2
      split: validation
    metrics:
    - type: exact_match
      value: 79.2432
      name: Exact Match
      verified: true
    - type: f1
      value: 82.336
      name: F1
      verified: true
  - task:
      type: question-answering
      name: Question Answering
    dataset:
      name: quoref
      type: quoref
      config: default
      split: validation
    metrics:
    - type: exact_match
      value: 78.8581
      name: Exact Match
      verified: true
    - type: f1
      value: 82.8261
      name: F1
      verified: true
---

<!-- 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. -->

# rob-base-superqa

This model is a fine-tuned version of [roberta-base](https://huggingface.co/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: 7e-05
- 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
- num_epochs: 3.0

### Training results



### Framework versions

- Transformers 4.21.1
- Pytorch 1.11.0a0+gita4c10ee
- Datasets 2.4.0
- Tokenizers 0.12.1