forked from huggingface/transformers
-
Notifications
You must be signed in to change notification settings - Fork 1
/
valohai.yaml
94 lines (93 loc) · 3.26 KB
/
valohai.yaml
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
---
- step:
name: Execute python examples/run_glue.py
image: pytorch/pytorch:nightly-devel-cuda10.0-cudnn7
command:
- python /valohai/repository/utils/download_glue_data.py --data_dir=/glue_data
- pip install -e .
- pip install -r examples/requirements.txt
- python examples/run_glue.py --do_train --data_dir=/glue_data/{parameter-value:task_name} {parameters}
parameters:
- name: model_type
pass-as: --model_type={v}
type: string
default: bert
- name: model_name_or_path
pass-as: --model_name_or_path={v}
type: string
default: bert-base-uncased
- name: task_name
pass-as: --task_name={v}
type: string
default: MRPC
- name: max_seq_length
pass-as: --max_seq_length={v}
description: The maximum total input sequence length after tokenization. Sequences longer than this will be truncated, sequences shorter will be padded.
type: integer
default: 128
- name: per_gpu_train_batch_size
pass-as: --per_gpu_train_batch_size={v}
description: Batch size per GPU/CPU for training.
type: integer
default: 8
- name: per_gpu_eval_batch_size
pass-as: --per_gpu_eval_batch_size={v}
description: Batch size per GPU/CPU for evaluation.
type: integer
default: 8
- name: gradient_accumulation_steps
pass-as: --gradient_accumulation_steps={v}
description: Number of updates steps to accumulate before performing a backward/update pass.
type: integer
default: 1
- name: learning_rate
pass-as: --learning_rate={v}
description: The initial learning rate for Adam.
type: float
default: 0.00005
- name: adam_epsilon
pass-as: --adam_epsilon={v}
description: Epsilon for Adam optimizer.
type: float
default: 0.00000001
- name: max_grad_norm
pass-as: --max_grad_norm={v}
description: Max gradient norm.
type: float
default: 1.0
- name: num_train_epochs
pass-as: --num_train_epochs={v}
description: Total number of training epochs to perform.
type: integer
default: 3
- name: max_steps
pass-as: --max_steps={v}
description: If > 0, set total number of training steps to perform. Override num_train_epochs.
type: integer
default: -1
- name: warmup_steps
pass-as: --warmup_steps={v}
description: Linear warmup over warmup_steps.
type: integer
default: -1
- name: logging_steps
pass-as: --logging_steps={v}
description: Log every X updates steps.
type: integer
default: 25
- name: save_steps
pass-as: --save_steps={v}
description: Save checkpoint every X updates steps.
type: integer
default: -1
- name: output_dir
pass-as: --output_dir={v}
type: string
default: /valohai/outputs
- name: evaluate_during_training
description: Run evaluation during training at each logging step.
type: flag
default: true
- name: do_lower_case
description: Set this flag if you are using an uncased model.
type: flag